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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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Stability of Kuramoto networks subject to large and small fluctuations from heterogeneous and spatially correlated noise

Oscillatory networks subjected to noise are broadly used to model physical and technological systems. Due to their nonlinear coupling, such networks typically have multiple stable and unstable states that a network might visit due to noise. In this article, we focus on the assessment of fluctuations resulting from heterogeneous and spatially correlated noise inputs on Kuramoto model networks. We evaluate the typical, small fluctuations near synchronized states and connect the network variance to the overlap between stable modes of synchronization and the input noise covariance. Going beyond small to large fluctuations, we introduce the indicator mode approximation that projects the dynamics onto a single amplitude dimension. Such an approximation allows for estimating rates of fluctuations to saddle instabilities, resulting in phase slips between connected oscillators. Statistics for both regimes are quantified in terms of effective noise amplitudes that are compared and contrasted for several noise models. In conclusion, bridging the gap between small and large fluctuations, we show that a larger network variance does not necessarily lead to higher rates of large fluctuations.

42 ENGINEERING↗
DOE OSTI2020

Modeling of the Coral Microbiome: the Influence of Temperature and Microbial Network

Host-associated microbial communities are shaped by extrinsic and intrinsic factors to the holobiont organism. Environmental factors and microbe-microbe interactions act simultaneously on the microbial community structure, making the microbiome dynamics challenging to predict. The coral microbiome is essential to the health of coral reefs and sensitive to environmental changes. Here, we develop a dynamic model to determine the microbial community structure associated with the surface mucus layer (SML) of corals using temperature as an extrinsic factor and microbial network as an intrinsic factor. The model was validated by comparing the predicted relative abundances of microbial taxa to the relative abundances of microbial taxa from the sample data. The SML microbiome from Pseudodiploria strigosa was collected across reef zones in Bermuda, where inner and outer reefs are exposed to distinct thermal profiles. A shotgun metagenomics approach was used to describe the taxonomic composition and the microbial network of the coral SML microbiome. By simulating the annual temperature fluctuations at each reef zone, the model output is statistically identical to the observed data. The model was further applied to six scenarios that combined different profiles of temperature and microbial network to investigate the influence of each of these two factors on the model accuracy. The SML microbiome was best predicted by model scenarios with the temperature profile that was closest to the local thermal environment, regardless of the microbial network profile. Our model shows that the SML microbiome of P. strigosa in Bermuda is primarily structured by seasonal fluctuations in temperature at a reef scale, while the microbial network is a secondary driver. Coral microbiome dysbiosis (i.e., shifts in the microbial community structure or complete loss of microbial symbionts) caused by environmental changes is a key player in the decline of coral health worldwide. Multiple factors in the water column and the surrounding biological community influence the dynamics of the coral microbiome. However, by including only temperature as an external factor, our model proved to be successful in describing the microbial community associated with the surface mucus layer (SML) of the coral P. strigosa. The dynamic model developed and validated in this study is a potential tool to predict the coral microbiome under different temperature conditions.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1978

Partially averaged field approach to cosmic ray diffusion

A new nonlinear technique is used to derive the kinetic equation for particles interacting with turbulent fluctuations. Difficulties associated with quasi-linear theory are avoided. The new method evaluates the effects of the fluctuations along particle orbits which themselves include the effects of a statistically averaged subset of the possible configuration of the turbulence. As an illustration, the pitch-angle diffusion coefficient is calculated for particles interacting with 'slab model' magnetic turbulence, i.e., magnetic fluctuations linearly polarized transverse to a mean magnetic field. The pitch-angle diffusion coefficient is determined in the vicinity of 90-deg pitch angles where quasi-linear theory breaks down. The spatial diffusion coefficient parallel to a mean magnetic field is evaluated by use of the calculated pitch-angle diffusion coefficient. It is suggested that the partially averaged field method is not limited to small amplitude fluctuating fields and hence is not a perturbation theory.

Jones, F. C.↗
NASA NTRS1995

Fractal mechanisms and heart rate dynamics. Long-range correlations and their breakdown with disease

Under healthy conditions, the normal cardiac (sinus) interbeat interval fluctuates in a complex manner. Quantitative analysis using techniques adapted from statistical physics reveals the presence of long-range power-law correlations extending over thousands of heartbeats. This scale-invariant (fractal) behavior suggests that the regulatory system generating these fluctuations is operating far from equilibrium. In contrast, it is found that for subjects at high risk of sudden death (e.g., congestive heart failure patients), these long-range correlations break down. Application of fractal scaling analysis and related techniques provides new approaches to assessing cardiac risk and forecasting sudden cardiac death, as well as motivating development of novel physiologic models of systems that appear to be heterodynamic rather than homeostatic.

NASA Discipline Cardiopulmonary↗
NASA NTRS1981

Kaman 40 kW wind turbine generator - control system dynamics

The generator design incorporates an induction generator for application where a utility line is present and a synchronous generator for standalone applications. A combination of feed forward and feedback control is used to achieve synchronous speed prior to connecting the generator to the load, and to control the power level once the generator is connected. The dynamics of the drive train affect several aspects of the system operation. These were analyzed to arrive at the required shaft stiffness. The rotor parameters that affect the stability of the feedback control loop vary considerably over the wind speed range encountered. Therefore, the controller gain was made a function of wind speed in order to maintain consistent operation over the whole wind speed range. The velocity requirement for the pitch control mechanism is related to the nature of the wind gusts to be encountered, the dynamics of the system, and the acceptable power fluctuations and generator dropout rate. A model was developed that allows the probable dropout rate to be determined from a statistical model of wind gusts and the various system parameters, including the acceptable power fluctuation.

Perley, R.↗
NASA NTRS2000

SNW 2000 Proceedings. Oxide Thickness Variation Induced Threshold Voltage Fluctuations in Decanano MOSFETs: a 3D Density Gradient Simulation Study

We use the density gradient (DG) simulation approach to study, in 3D, the effect of local oxide thickness fluctuations on the threshold voltage of decanano MOSFETs in a statistical manner. A description of the reconstruction procedure for the random 2D surfaces representing the 'atomistic' Si-SiO2 interface variations is presented. The procedure is based on power spectrum synthesis in the Fourier domain and can include either Gaussian or exponential spectra. The simulations show that threshold voltage variations induced by oxide thickness fluctuation become significant when the gate length of the devices become comparable to the correlation length of the fluctuations. The extent of quantum corrections in the simulations with respect to the classical case and the dependence of threshold variations on the oxide thickness are examined.

Asenov, Asen↗
DOE OSTI2023

Fluctuations in heavy ion collisions and global conservation effects

Subensemble is a type of statistical ensemble which is the generalization of grand canonical and canonical ensembles. The subensemble acceptance method (SAM) provides general formulas to correct the cumulants of distributions in heavy-ion collisions for the global conservation of all QCD charges. The method is applicable for an arbitrary equation of state and sufficiently large systems, such as those created in central collisions of heavy ions. The new fluctuation measures insensitive to global conservation effects are presented. The main results are illustrated in the hadron resonance gas and van der Waals fluid frameworks.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS1993

Coherent lidar design and performance verification

The verification of LAWS beam alignment in space can be achieved by a measurement of heterodyne efficiency using the surface return. The crucial element is a direct detection signal that can be identified for each surface return. This should be satisfied for LAWS but will not be satisfied for descoped LAWS. The performance of algorithms for velocity estimation can be described with two basic parameters: the number of coherently detected photo-electrons per estimate and the number of independent signal samples per estimate. The average error of spectral domain velocity estimation algorithms are bounded by a new periodogram Cramer-Rao Bound. Comparison of the periodogram CRB with the exact CRB indicates a factor of two improvement in velocity accuracy is possible using non-spectral domain estimators. This improvement has been demonstrated with a maximum-likelihood estimator. The comparison of velocity estimation algorithms for 2 and 10 micron coherent lidar was performed by assuming all the system design parameters are fixed and the signal statistics are dominated by a 1 m/s rms wind fluctuation over the range gate. The beam alignment requirements for 2 micron are much more severe than for a 10 micron lidar. The effects of the random backscattered field on estimating the alignment error is a major problem for space based lidar operation, especially if the heterodyne efficiency cannot be estimated. For LAWS, the biggest science payoff would result from a short transmitted pulse, on the order of 0.5 microseconds instead of 3 microseconds. The numerically errors for simulation of laser propagation in the atmosphere have been determined as a joint project with the University of California, San Diego. Useful scaling laws were obtained for Kolmogorov atmospheric refractive turbulence and an atmospheric refractive turbulence characterized with an inner scale. This permits verification of the simulation procedure which is essential for the evaluation of the effects of refractive turbulence on coherent Doppler lidar systems. The analysis of 2 micron Doppler lidar data from Coherent Technologies, Inc. (CTI) has demonstrated many of the advantages of doppler lidar measurements of boundary layer winds. The effects of wind shear and wind turbulence over the pulse volume are probably the dominant source of the reduced performance. The effects of wind shear and wind turbulence on the statistical description of doppler lidar data has been derived and calculated.

Frehlich, Rod↗
NASA NTRS1981

A stochastic-dynamical approach to the study of the natural variability of the climate

A method, suggested by Leith (1975), which employed stochastic-dynamic forecasts obtained from a general circulation model in such a way as to satisfy the definition of climatic noise, was used to validate assumptions accounting for the effects of external influences in estimating the climatic noise. Two assumptions were investigated: (1) that the weather fluctuations can be represented as a Markov process, and (2) that changing external conditions do not influence the atmosphere's statistical properties on short time scales. The general circulation model's simulation of the daily weather fluctuations was generated by performing integrations with prescribed climatological boundary conditions for random initial atmospheric states, with resulting dynamical forecasts providing an ensemble of simulated data for the autoregressive modeling of weather fluctuations. To estimate the climatic noise from the observational data (consisting of hourly values of sea level pressure and surface temperature at 54 U.S. stations for the month of January for the years 1949-1975) use of the short time-scale assumption is made. The simulated and observed data were found not to be consistent with either white noise or a Markov process of weather fluctuations. Good agreement was found between the results of the hypothetical testing of the simulated and the observed surface temperatures; and only partial support was found for the short time-scale assumption, i.e., for sea level pressure.

Straus, D. M.↗
NASA NTRS1986

Statistical properties and correlation functions for drift waves

The dissipative one-field drift wave equation is solved using the pseudospectral method to generate steady-state fluctuations. The fluctuations are analyzed in terms of space-time correlation functions and modal probability distributions. Nearly Gaussian statistics and exponential decay of the two-time correlation functions occur in the presence of electron dissipation, while in the absence of electron dissipation long-lived vortical structures occur. Formulas from renormalized, Markovianized statistical turbulence theory are given in a local approximation to interpret the dissipative turbulence.

Horton, W.↗
DOE OSTI2023

Lagrangian statistics of a shock-driven turbulent dynamo in decaying turbulence

Small-scale fluctuating magnetic fields of order nG are observed in supernova shocks and galaxy clusters, where its amplification is likely caused by the Biermann battery mechanism. However, these fields cannot be amplified further without the turbulent dynamo, which generates magnetic energy through the stretch-twist-fold (STF) mechanism. Thus, we present here novel 3D magnetohydrodynamic (MHD) simulations of a laser-driven shock propagating into a stratified, multiphase medium, to investigate the post-shock turbulent magnetic field amplification via the turbulent dynamo. The configuration used here is currently being tested in the shock tunnel at the National Ignition Facility (NIF). In order to probe the statistical properties of the post-shock turbulent region, we use 384 × 512 × 384 tracers to track its evolution through the Lagrangian framework, thus providing a high-fidelity analysis of the shocked medium. Our simulations indicate that the growth of the magnetic field, which accompanies the near-Saffman kinetic energy decay (E kin ∝ t -1.15 ) without turbulence driving, exhibits slightly different characteristics as compared to periodic box simulations. Seemingly no distinct phases exist in its evolution because the shock passage and time to observe the magnetic field amplification during the turbulence decay are very short (~0.3 of a turbulent turnover time). Yet, the growth rate is still consistent with those expected for compressive (curl-free) turbulence driving in subsonic, compressible turbulence. Phenomenological understanding of the dynamics of the magnetic and velocity fields are also elucidated via Lagrangian frequency spectra, which are consistent with the expected inertial range scalings in the Eulerian–Lagrangian bridge.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Coherent Random Lasing in Subwavelength Quasi‐2D Perovskites

Abstract Quasi‐2D lead halide perovskites have garnered increasing interest as lasing gain media. Relatively simple fabrication, high refractive index, and unique quantum well structure encourage their use in traditional cavity lasers and cavity‐free systems called random lasers (RLs). Despite tremendous advances reported thus far, coherent random lasing in quasi‐2D perovskite subwavelength films has not been reported. Consequently, coherent optical feedback mechanisms in quasi‐2D perovskite systems are still unexplored. Here, this work reports the observation of coherent random lasing in subwavelength quasi‐2D perovskite films. Statistical analysis of spectral measurements reveals Lévy‐like intensity fluctuations, replica symmetry breaking confirms random lasing, and the coherent modes are studied with spectral and spatial correlation techniques. The observed coherent lasing modes are found to be extended states that arise from the random crystal grain structure during fabrication and span the entire pump volume. These modes out‐compete diffusive lasing due to their coherence.

47 OTHER INSTRUMENTATION↗
DOE OSTI2026

Data-driven particle dynamics: Structure-preserving coarse-graining for emergent behavior in non-equilibrium systems

Multiscale systems are ubiquitous in science and technology, but are notoriously challenging to simulate as short spatiotemporal scales must be appropriately linked to emergent bulk physics. When expensive high-dimensional dynamical systems are coarse-grained into low-dimensional models, the entropic loss of information leads to emergent physics which are dissipative, history-dependent, and stochastic. To machine learn coarse-grained dynamics from time-series observations of particle trajectories, we propose a framework using the metriplectic bracket formalism that preserves these properties by construction; most notably, the framework guarantees discrete notions of the first and second laws of thermodynamics, conservation of momentum, and a discrete fluctuation-dissipation balance crucial for capturing non-equilibrium statistics. We introduce the mathematical framework abstractly before specializing to a particle discretization. As labels are generally unavailable for entropic state variables, we introduce a novel self-supervised learning strategy to identify emergent structural variables. We validate the method on benchmark systems and demonstrate its utility on two challenging examples: (1) coarse-graining star polymers at challenging levels of coarse-graining while preserving non-equilibrium statistics, and (2) learning models from high-speed video of colloidal suspensions that capture coupling between local rearrangement events and emergent stochastic dynamics. We provide open-source implementations in both PyTorch and LAMMPS, enabling large-scale inference and extensibility to diverse particle-based systems.

Computational Engineering, Finance, and Science (c↗
NASA NTRS1980

An error analysis of basic kinematic quantities

A description is presented of the computational procedures used to obtain spatial fields of relative vorticity, advection of vorticity, horizontal divergence, and vertical motion. An investigation is conducted of the effectiveness of these procedures to reduce the effects of deliberately introduced random errors, giving attention to the confidence which can be placed on values of the derived parameters. It is concluded that fields of 500 mb vorticity and 700 mb vertical velocity, which are frequently used in synoptic scale forecasting schemes, show minimal effects of the deliberately introduced errors. Vorticity advection is found to be the most sensitive term to input data errors. Large fluctuations in fields of this parameter are evident both statistically and qualitatively.

Berecek, E. M.↗
NASA NTRS1982

Crop classification using airborne radar and Landsat data

NASA 13.3 GHz airborne radar data from a soil moisture measurement analysis is used to investigate the statistical nature of the radar backscattering coefficient for bare ground and three different crop types, and to evaluate the crop classification rates using Landsat data alone or combined with the airborne survey. The scatterometer was a fan-beam Doppler system, VV polarized, and is considered only for 50 deg angles of incidence. A total of 36 fields were covered a week apart by the aircraft and Landsat, and Rayleigh statistics were used in the frequency averaging to eliminate fluctuations due to random fluctuations. Within-field variances were calculated for the Landsat and the radar data and used to design optimum crop classification procedures. The Landsat Band 4 readings were 67% accurate, and an increase in accuracy of 10% was achieved by the addition of the radar data.

Ulaby, F. T.↗