SEARCH · Search NASA

Results for “dynamic parameter estimation”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,423 records · Page 79

All sources NASA NTRS DOE OSTI

DOE OSTI2022

Estimation of the time for steam generator trip due to cyber intrusions

The time required to trip a pressurized water reactor (PWR) by inserting malicious signals into its steam generator (SG) control system has been studied using the Generic PWR (GPWR) Simulator. A semi-analytical model is developed to approximately reproduce the simulator response and understand the dynamics of the control unit. A series of two proportional-integral controllers determines control action according to preset constants, the readings from the feedwater level sensor, and those from feedwater and steam flowrate transmitters. It is observed that the most important factor that determines whether a trip will occur is how much additional water is added to or withheld from the SG over time compared to normal operating conditions. In order to determine the effects of control action on the SG, changes in mass inventory are considered. This approach models the SG water level as a function of mass inventory and has a backward temporal memory. A Python interface is developed for the GPWR framework to automatically simulate different spoofing scenarios and post-process the related data. We observe that the trip times predominantly depend on flow mismatch and/or level errors. Controller parameters, including the integral time and gain constants, either speed up or slow down the rate of progression to a trip setpoint but do not cause a trip by themselves. The reactor can trip on a high-level signal when the reading crosses above 78%, increased from its reference level of 57%, or a low-level reading when it is below 25%. The present results show roughly how long the operators would have to respond to an attack, given a specific set of spoofing signals within the issue space analyzed. Furthermore, we have generated a simple surface by fitting a combination of exponential functions to the data obtained from the GPWR Simulator. In general, trips on a low level have been observed to occur faster than those on a high level.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2025

Real-Time Wave Energy Converter Control Using Instantaneous Frequency

Wave Energy Converters (WECs) rely on effective Power Take-Off (PTO) control strategies to maximize energy absorption under dynamic sea conditions. Traditional hydrodynamic modeling techniques may require computationally intensive convolution calculations, making real-time control implementation challenging. This paper presents an alternative approach by leveraging instantaneous frequency estimation to dynamically adjust PTO damping in response to varying wave frequencies. Two real-time frequency estimation methods are explored: the Hilbert Transform (HT) and Phase-Locked Loop (PLL). The Hilbert Transform method provides accurate frequency tracking but introduces a delayed response due to its dependence on causal data. Conversely, the PLL approach demonstrates strong potential in frequency tracking but requires careful gain tuning, particularly in complex sea states. Comparative evaluations across multiple test cases—including sinusoidal variations, amplitude steps, frequency step changes, and real-world JONSWAP spectrum waves—highlight the strengths and limitations of each method. The two different PTO control techniques across the various frequency estimation methods were tested under real-sea states using a state-space model of a point-absorbing Wave Energy Converter. The Capture Width Ratio (CWR) is used as a performance metric, with results showing that the HT achieves a 10.6% improvement, while the PLL estimation yields a 0.9% improvement relative to the fixed parameter control baseline. These results highlight the effectiveness of real-time frequency estimation in improving energy absorption compared to static control parameters.

WEC control↗

DOE OSTI2020

An Investigation of Poorly Studied Open Cluster NGC 4337 Using Multicolor Photometric and Gaia DR2 Astrometric Data

We present a comprehensive analysis (photometric and kinematical) of the poorly studied open cluster NGC 4337 using 2MASS, WISE, APASS, and Gaia DR2 databases. By determining the membership probabilities of stars, we identified the 624 most probable members with membership probability higher than 50% by using proper motion and parallax data taken from Gaia DR2. The mean proper motion of the cluster is obtained as μ{sub x}=−8.83±0.01 and μ {sub y} = 1.49 ± 0.006 mas yr{sup −1}. We find the normal interstellar extinction toward the cluster region. The radial distribution of members provides a cluster radius of 7.′75 (5.63 pc). The estimated age of 1600 ± 180 Myr indicates that NGC 4337 is an old open cluster with a bunch of red giant stars. The overall mass function slope for main-sequence stars is found as 1.46±0.18 within the mass range 0.75−2.0 M{sub ⊙}, which is in fair agreement with Salpeter’s value (x = 1.35) within uncertainty. The present study demonstrates that NGC 4337 is a dynamically relaxed open cluster. Using the Galactic potential model, Galactic orbits are obtained for NGC 4337. We found that this object follows a circular path around the Galactic center. Under the kinematical analysis, we compute the apex coordinates (A, D) by using two methods: (i) the classical convergent point method and (ii) the AD-diagram method. The obtained coordinates are (A {sub conv}, D {sub conv}) = (96.°27 ± 0.°10, 13.°14 ± 0.°27) and (A {sub ◦}, D {sub ◦}) = (100.°282 ± 0.°10, 9.°577 ± 0.°323) respectively. We also computed the Velocity Ellipsoid Parameters, matrix elements (μ {sub ij}), direction cosines (l {sub j}, m {sub j}, n {sub j}), and the Galactic longitude of the vertex (l {sub 2}).

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2022

Development of an open-source regional data assimilation system in PEcAn v. 1.7.2: application to carbon cycle reanalysis across the contiguous US using SIPNET

Abstract. The ability to monitor, understand, and predict the dynamics of the terrestrial carbon cycle requires the capacity to robustly and coherently synthesize multiple streams of information that each provide partial information about different pools and fluxes. In this study, we introduce a new terrestrial carbon cycle data assimilation system, built on the PEcAn model–data eco-informatics system, and its application for the development of a proof-of-concept carbon “reanalysis” product that harmonizes carbon pools (leaf, wood, soil) and fluxes (GPP, Ra, Rh, NEE) across the contiguous United States from 1986–2019. We first calibrated this system against plant trait and flux tower net ecosystem exchange (NEE) using a novel emulated hierarchical Bayesian approach. Next, we extended the Tobit–Wishart ensemble filter (TWEnF) state data assimilation (SDA) framework, a generalization of the common ensemble Kalman filter which accounts for censored data and provides a fully Bayesian estimate of model process error, to a regional-scale system with a calibrated localization. Combined with additional workflows for propagating parameter, initial condition, and driver uncertainty, this represents the most complete and robust uncertainty accounting available for terrestrial carbon models. Our initial reanalysis was run on an irregular grid of ∼ 500 points selected using a stratified sampling method to efficiently capture environmental heterogeneity. Remotely sensed observations of aboveground biomass (Landsat LandTrendr) and leaf area index (LAI) (MODIS MOD15) were sequentially assimilated into the SIPNET model. Reanalysis soil carbon, which was indirectly constrained based on modeled covariances, showed general agreement with SoilGrids, an independent soil carbon data product. Reanalysis NEE, which was constrained based on posterior ensemble weights, also showed good agreement with eddy flux tower NEE and reduced root mean square error (RMSE) compared to the calibrated forecast. Ultimately, PEcAn's new open-source regional data assimilation framework provides a scalable workflow for harmonizing multiple data constraints and providing a uniform synthetic platform for carbon monitoring, reporting, and verification (MRV) as well as accelerating terrestrial carbon cycle research.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1987

Development of response models for the Earth Radiation Budget Experiment (ERBE) sensors. Part 1: Dynamic models and computer simulations for the ERBE nonscanner, scanner and solar monitor sensors

Dynamic models and computer simulations were developed for the radiometric sensors utilized in the Earth Radiation Budget Experiment (ERBE). The models were developed to understand performance, improve measurement accuracy by updating model parameters and provide the constants needed for the count conversion algorithms. Model simulations were compared with the sensor's actual responses demonstrated in the ground and inflight calibrations. The models consider thermal and radiative exchange effects, surface specularity, spectral dependence of a filter, radiative interactions among an enclosure's nodes, partial specular and diffuse enclosure surface characteristics and steady-state and transient sensor responses. Relatively few sensor nodes were chosen for the models since there is an accuracy tradeoff between increasing the number of nodes and approximating parameters such as the sensor's size, material properties, geometry, and enclosure surface characteristics. Given that the temperature gradients within a node and between nodes are small enough, approximating with only a few nodes does not jeopardize the accuracy required to perform the parameter estimates and error analyses.

Halyo, Nesim↗

DOE OSTI2021

Film Thickness and Composition Effects in Symmetric Ternary Block Copolymer/Homopolymer Blend Films: Domain Spacing and Orientation

We report thickness and homopolymer molar mass dependencies in thin film blends of a compositionally symmetric 75 kg/mol lamellar polystyrene-block-poly(methyl methacrylate) diblock copolymer (PS-b-PMMA) with near-equal volume fractions of PS and PMMA homopolymers on “neutral” surfaces that promote a vertical domain orientation. PS and PMMA homopolymers with equal molar masses of 1, 3, and 22 kg/mol are blended in a 1:1 mass ratio. To efficiently explore this parameter space, we prepared combinatorial samples with gradient homopolymer concentrations using electrospray deposition (ESD) and gradient film thicknesses using flow coating; these samples were subsequently characterized by grazing-incidence small-angle X-ray scattering and scanning electron microscopy, respectively. Our results demonstrate that the added homopolymers increase or reduce domain spacings with respect to the neat (unblended) block copolymer depending on their molar masses, in line with previous reports; a simple heuristic to estimate the domain scaling in ternary blends based on the homopolymer molar mass agrees well with data for the thinnest blend films studied here. More surprisingly, we observe that the measured domain spacing in blends also depends on film thickness, with thicker films exhibiting larger domain spacings than thinner films at the same homopolymer concentration. Furthermore, thickness gradients at fixed homopolymer concentrations reveal a change in lamellae orientation from vertical to horizontal as film thickness is increased beyond the nominal lamellar domain spacing. Coarse-grained molecular dynamics simulations indicate that this change in orientation is induced by homopolymer segregation to film surfaces. Finally, tying these effects together, we hypothesize that the observed dependence of domain spacing on film thickness is a consequence of changes in the vertical homopolymer composition profile in thicker films during lamellae reorientation and the conformational asymmetry between PMMA and PS segments.

36 MATERIALS SCIENCE↗

NASA NTRS1994

Overview of the Oregon Transect Ecosystem Research Project

The Oregon Transect Ecosystem Research (OTTER) project is a study of ecosystem functions in coniferous forests using the methods of computer modeling, experimental and theoretical remote sensing, and ecological field and laboratory techniques. The study is focused on predicting the major fluxes of carbon, nitrogen, and water, and the factors that dynamically regulate them. The OTTER project was conceived to test two major questions: (1) Can a generalized ecosystem simulation model, designed to use mainly parameters available from remote sensing, predict the functioning of forests across an environmentally variable region? and (2) To what extent can the variables required by this model be derived from remotely sensed data? The scientific objectives and scope of the project demanded that a coordinated effort be made to link ground measurements with remote sensing and modeling requirements. OTTER was selected as a focus for a National Aeronautics and Space Administration (NASA)-sponsored Multi-sensor Aircraft Campaign (MAC; combining NASA aircraft and sensors with those of others) on the basis of experience gained in past ecosystem studies and remote-sensing projects, and the importance of the OTTER objectives to NASA's long-range science goals and plans. Having several independent approaches available, both on the ground and from various remote-sensing platforms, proved valuable in estimating and validating many of the critical variables. This experience and cross comparison should help simplify future studies of a similar nature. Edited data sets from the OTTER project are now available to the scientific community on optical disks or via on-line data banks at NASA (Washington, D.C., USA) and Oregon State University (Corvallis, Oregon, USA).

Peterson, David L.↗

NASA NTRS2006

Variations in the Sea Ice Edge and the Marginal Ice Zone on Different Spatial Scales as Observed from Different Satellite Sensor

The Marginal sea Ice Zone (MIZ) and the sea ice edge are the most dynamic areas of the sea ice cover. Knowledge of the sea ice edge location is vital for routing shipping in the polar regions. The ice edge is the location of recurrent plankton blooms, and is the habitat for a number of animals, including several which are under severe ecological threat. Polar lows are known to preferentially form along the sea ice edge because of induced atmospheric baroclinicity, and the ice edge is also the location of both vertical and horizontal ocean currents driven by thermal and salinity gradients. Finally, sea ice is both a driver and indicator of climate change and monitoring the position of the ice edge accurately over long time periods enables assessment of the impact of global and regional warming near the poles. Several sensors are currently in orbit that can monitor the sea ice edge. These sensors, though, have different spatial resolutions, different limitations, and different repeat frequencies. Satellite passive microwave sensors can monitor the ice edge on a daily or even twice-daily basis, albeit with low spatial resolution - 25 km for the Special Sensor Microwave Imager (SSM/I) or 12.5 km for the Advanced Microwave Scanning Radiometer (AMSR-E). Although special methods exist that allow the detection of the sea ice edge at a quarter of that nominal resolution (PSSM). Visible and infrared data from the Advanced Very High Resolution Radiometer (AVHRR) and from the Moderate Resolution Imaging Spectroradiometer (MODIS) provide daily coverage at 1 km and 250 m, respectively, but the surface observations me limited to cloud-free periods. The Landsat 7 Enhanced Thematic Mapper (ETM+) has a resolution of 15 to 30 m but is limited to cloud-free periods as well, and does not provide daily coverage. Imagery from Synthetic Aperture Radar (SAR) instruments has resolutions of tens of meters to 100 m, and can be used to distinguish open water and sea ice on the basis of surface and volume scattering characteristics. The Canadian RADARSAT C-band SAR provides data that cover the Arctic Ocean and the MIZ every 3 days. A change-point detection approach was utilized to obtain an ice edge estimate from the RADARSAT data The Quickscat scatterometer provides ice edge information with a resolution of a few kilometers on a near-daily basis. During portions of March and April of 2003 a series of aircraft flights were conducted over the ice edge in the Bering Sea carrying the Polarimetric Scanning Radiometer (PSR), which provides spectral coverage identical with the AMSR-E instrument at a resolution of 500 meters. In this study we investigated these different data sets and analyzed differences in their definition of the sea ice edge and the marginal ice zone and how these differences as well as their individual limitations affect the monitoring of the ice edge dynamics. We also examined how the nature of the sea ice edge, including its location, compactness and shape, changes over the seasons. Our approach was based on calculation of distances between ice edges derived from the satellite and aircraft data sets listed above as well as spectral coherence methods and shape parameters such as tortuosity, curvature, and fractional dimension.

Markus, Thorsten↗

NASA NTRS2020

Spectral Range Within Global aCDOM(440) Algorithms for Oceanic, Coastal, and Inland Waters with Application to Airborne Measurements

The optically active component of dissolved organic material in aquatic ecosystems, or colored dissolved organic matter (CDOM), is represented by the coefficient of absorption due to the dissolved aquatic constituents at 440 nm, aCDOM(440). Remote sensing of aCDOM(440) enables characterization of ecosystem processes and aids in retrieval of chlorophyll a, a proxy for phytoplankton biomass. Spectrally adjacent band-ratio domains, e.g., blue to green, have previously been applied for remote sensing of aCDOM(440) in coastal and oceanic waters with similar results compared to more complex semi-analytical algorithms. Estimation of aCDOM(440) from ratios of the most spectrally separated ocean color wavebands (end members), e.g., ultraviolet (UV) to near-infrared (NIR), termed end-member analysis (EMA), has previously been shown to increase the accuracy of global aCDOM(440) retrievals from in-water observations of diffuse attenuation and to enable a unified algorithmic perspective without requiring regional adjustment of internal bio-optical parameters. EMA of above-water observations is evaluated herein, with a focus on coastal and inland waters in which increasing optical complexity and likelihood of bottom reflectance challenge the oceanic algorithms developed for deep and optically simple (case-1) waters. Analysis herein of three independent, in situ, bio-optical datasets indicates significant correlation between aCDOM(440) and end-member band ratios (next-generation 320 and 780 nm or legacy 412 and 670 nm ratios) with a coefficient of determination, R2, of 0.87 (log-scale) or higher based on a dataset spanning the dynamic range of global, conservative water bodies. For applicable wavelengths, EMA algorithms are shown to agree with case-1 relationships and to produce consistent log-scale uncertainties across more than three orders of magnitude in aCDOM(440) values (0.001–2.305 m􀀀1). EMA using UV and NIR wavelengths (320 and 780 nm) is applied to low-altitude airborne observations and satisfies 25% uncertainty based on unbiased percent differences (UPDs) within each of three dissimilar match-up sites ranging in aCDOM(440) from 0.02–0.57 m􀀀1. Results demonstrate that EMA is a useful and robust approach for the remote sensing of aCDOM(440) in coastal and inland waters, which are generally shallower, contain more optically complex environments, and span a greater range in aCDOM(440) than oceanic waters.

CDOM↗

NASA NTRS1994

A coronal mass ejection model for the 1992 July 15 flare on AU Microscopii observed by the extreme ultraviolet explorer

The dM1e flare star AU Microscopii (AU Mic) was observed by the EUVE Deep Survey Instrument on 1992 July 14-18. A large flare was detected in the Deep Survey Lexan/Boron (DS Lex/B)(65-190 A) band and the SW (70-190 A) and MW (140-380 A) spectrometers. The flare consisted of a sharp impulsive peak lasting approximately 2 hours followed by a decaying tail lasting about a day. We present a simple, single temperature, dynamic model for the flare decay which is consistent with the DS Lex/B light curve and reproduces the strongest, high-temperature spectral lines in the released EUVE spectra. In this model, we assume the long decay time is due to an ejected, magnetically confined, low beta plasmoid expanding self similarly in the ambient medium in a manner reminiscent of solar coronal mass ejections. We demonstrate that the long tail of the DS Lex/B light curve can be explained by rapid expansion, causing the plasma to become tenuous sufficiently quickly that it avoids catastrophic radiative cooling. From this model, we estimate the mass of the plasmoid to be approximately = 10(exp 20) g and the total energy of the event to be approximately = 10(exp 36) ergs. These values are approximately 10(exp 4) times as large as those seen during the largest solar coronal mass ejection (CME) events. We argue that the results of our model are consistent with other measurements of stellar flare parameters. We also estimate a mass-loss rate of a few times 10(exp -13) Solar mass/yr and discuss the role of mass loss from dMe stars in the mass balance of the interstellar medium. We estimate the rotational braking timescale from these events to be less than 500 million years and suggest that CME's may be an important source of angular momentum loss from late-type stars.

Cully, Scott L.↗

DOE OSTI2019

Asymptotic Behavior of Memristive Circuits

The interest in memristors has risen due to their possible application both as memory units and as computational devices in combination with CMOS. This is in part due to their nonlinear dynamics, and a strong dependence on the circuit topology. We provide evidence that also purely memristive circuits can be employed for computational purposes. In the present paper we show that a polynomial Lyapunov function in the memory parameters exists for the case of DC controlled memristors. Such a Lyapunov function can be asymptotically approximated with binary variables, and mapped to quadratic combinatorial optimization problems. This also shows a direct parallel between memristive circuits and the Hopfield-Little model. In the case of Erdos-Renyi random circuits, we show numerically that the distribution of the matrix elements of the projectors can be roughly approximated with a Gaussian distribution, and that it scales with the inverse square root of the number of elements. This provides an approximated but direct connection with the physics of disordered system and, in particular, of mean field spin glasses. Using this and the fact that the interaction is controlled by a projector operator on the loop space of the circuit. We estimate the number of stationary points of the approximate Lyapunov function and provide a scaling formula as an upper bound in terms of the circuit topology only.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS2006

Diurnal Variability of Vertical Structure from a TRMM Passive Microwave "Virtual Radar" Retrieval

Robust description of the diurnal cycle from TRMM observations is complicated by the limitations of Low Earth Orbit (LEO) sampling; from a 'climatological' perspective, sufficient sampling must exist to control for both spatial and seasonal variability, before tackling an additional diurnal component (e.g., with 8 additional 3-hourly or 24 1-hourly bins). For documentation of vertical structure, the narrow sample swath of the TRMM Precipitation Radar limits the resolution of any of these components. A neural-network based 'virtual radar" retrieval has been trained and internally validated, using multifrequency / multipolarization passive microwave(TM1) brightness temperatures and textures parameters and lightning (LIS) observations, as inputs, and PR volumetric reflectivity as targets (outputs). By training the algorithms (essentially highly multivariate, nonlinear regressions) on a very large sample of high-quality co-located data from the center of the TRMM swath, 3D radar reflectivity and derived parameters (VIL, IWC, Echo Tops, etc.) can be retrieved across the entire TMI swath, good to 8-9% over the dynamic range of parameters. As a step in the retrieval (and as an output of the process), each TMI multifrequency pixel (at 85 GHz resolution) is classified into one of the 25 archetypal radar profile vertical structure "types", previously identified using cluster analysis. The dynamic range of retrieved vertical structure appears to have higher fidelity than the current (Version 6) experimental GPROF hydrometeor vertical structure retrievals. This is attributable to correct representation of the prior probabilities of vertical structure variability in the neural network training data, unlike the GPROF cloud-resolving model training dataset used in the V6 algorithms. The LIS lightning inputs are supplementary inputs, and a separate offline neural network has been trained to impute (predict) LIS lightning from passive-microwave-only data. The virtual radar retrieval is thus, in principle, extensible to Aqua/AMSR-E and NPOESS/CMIS passive microwave instruments. The virtual radar approach yields a threefold increase in effective sampling from the mission, albeit of lower-quality "retrieved" data, reducing the variance of local estimates by one third (or the standard deviation by-0.57). In this talk, the variance reduction is leveraged to more finely resolve global diurnal variability in both space and time (local hour).

Boccippio, Dennis J.↗

NASA NTRSDate not supplied

Communication Demand in the National Airspace - A Federated Learning Approach

Within the national airspace system (NAS), efficient use of spectrum remains a challenge; as UAS and UAM missions evolve, the amount of mission-critical aircraft communications are expected to significantly grow. To accommodate the increased demand, NASA Glenn Research Center is investigating artificial intelligence approaches that could dynamically allocate spectrum; however, these solutions are driven by communication and aviation data items, many of which are not directly available. One such cornerstone data item is communication demand, parameterizing the needs within a sector in terms that may directly inform spectrum allocation, such as channel access duration, bandwidth, and modulation type. This paper considers the complexity of predicting communication demand as a function of NAS behaviors. Unlike prior prediction work in communications, this research must consider how the NAS may be impacted by external factors - such as convective weather and closures - rather than estimating demand from time-series forecasting alone. Much of this research considers a federated learning design to predict communication events in terms of the type of event occurring (sector coordination, conflict resolution, etc.). To do so, an investigation of products from Sherlock Data Warehouse is conducted, identifying the trends, sufficiency, and correlations of each product to identified events. Additionally, a preliminary discussion for inferring associations between these event types and their communication parameters (duration, bandwidth, modulation) is presented. By utilizing federated learning, imbalances in the types of events and data present throughout the NAS can inform local models without impairing global training. Furthermore, the two-stage approach proposed allows for robust and speculative communication modelling, as communication techniques continue to evolve. As a result, this model enables a generalized approach to understanding NAS communications which is able to inform long-term changes to aviation spectrum management.

Nathan Schimpf↗

NASA NTRSDate not supplied

A Federated Learning Approach to Predicting Communication Demand in the National Airspace

Within the national airspace system (NAS), efficient use of spectrum remains a challenge; as UAS and UAM missions evolve, the amount of mission-critical aircraft communications are expected to significantly grow. To accommodate the increased demand, NASA Glenn Research Center is investigating artificial intelligence approaches that could dynamically allocate spectrum; however, these solutions are driven by communication and aviation data items, many of which are not directly available. One such cornerstone data item is communication demand, parameterizing the needs within a sector in terms that may directly inform spectrum allocation, such as channel access duration, bandwidth, and modulation type. This paper considers the complexity of predicting communication demand as a function of NAS behaviors. Unlike prior prediction work in communications, this research must consider how the NAS may be impacted by external factors - such as convective weather and closures - rather than estimating demand from time-series forecasting alone. Much of this research considers a federated learning design to predict communication events in terms of the type of event occurring (sector coordination, conflict resolution, etc). To do so, an investigation of products from Sherlock Data Warehouse is conducted, identifying the trends, sufficiency, and correlations of each product to identified events. Additionally, a preliminary discussion for inferring associations between these event types and their communication parameters (duration, bandwidth, modulation) is presented. By utilizing federated learning, imbalances in the types of events and data present throughout the NAS can inform local models without impairing global training. Furthermore, the two-stage approach proposed allows for robust and speculative communication modelling, as communication techniques continue to evolve. As a result, this model enables a generalized approach to understanding NAS communications which is able to inform long-term changes to aviation spectrum management.

Nathan Schimpf↗

DOE OSTI2020

Performance estimation of resonance-enhanced dual-buoy wave energy converter using coupled time-domain simulation

This article presents the modeling methodology and performance evaluation of the resonance-enhanced dual-buoy WEC (Wave Energy Converter) by HEM (hydrodynamic & electro-magnetic) fully-coupled-dynamics time-domain-simulation program. The numerical results are systematically compared with the authors’ 1/6-scale experiment. With a direct-drive linear generator, the WEC consists of dual floating cylinders and a moon-pool between the cylinders, which can utilize three resonance phenomena from moon-pool dynamics as well as heave motions of inner and outer buoys. The contact and friction between the two buoys observed in the experiment are also properly modeled in the time-domain simulation by the Coulomb-friction model. Moon-pool resonance peaks significantly exaggerated in linear potential theory are empirically adjusted through comparisons with measured values. A systematic comparative study between the simulations and experiments with and without PTO (power-take-off) is conducted, and the relative heave displacements/velocities and power outputs are well matched. Then, parametric studies are carried out with the simulation program to determine optimum generator parameters. The performance with various wave conditions is also assessed.

16 TIDAL AND WAVE POWER↗

DOE OSTI2019

Hyper-Velocity Nanoparticle Plasma Jet as Fast Probe for Runaway Electrons in Tokamak Disruptions

The large energy focalized deposition of the runaway electron (RE) beam on the first wall can potentially yield to destructive effects on the reactor vessel during the explosive instability of a major disruption in a large tokamak (e.g. RE beam estimation is multi-MA of ~10 MeV energy in ITER.) Impurity injection is seen as an effective way to suppress REs after thermal quench (TQ). Injected material in solid state is advantageous, but it must be in small size grain form, with large surface-to-mass ratio to facilitate its rapid ablation within plasma. However, the results using shattered pellet injection (SPI), a technique aiming to satisfy these condition, indicated that the relatively unexplored RE evolution phases and RE beam-plasma interaction are far from being properly diagnosed and fully understood. We proposed the idea to probe REs with a pulsed power hyper-velocity large-mass nanoparticle plasma jet (NPPJ). NPPJ provides a high specific surface area and swift injection to core, hence fast increase of three basic parameters: 1) the electron density ne (bound and free through ionization, if the cold post-TQ plasma has a still high enough T e ), 2) the effective charge (Z eff ) which rises both the dynamical friction force and plasma resistivity, and, finally, 3) the value of the (Dreicer and critical) threshold E-field above which electrons are accelerated and become REs. But the fast transient phenomena of RE ”seed” creation, RE ”avalanche” multiplication, and RE beam formation and interaction with the background plasma all take place dominantly in the core plasma, where the induction E-field has its maximum. Thus, the RE probe success requires a rapid (1 - 2 ms) injection of sufficient mass able to penetrate through the strong toroidal magnetic field (2 - 5 T) over a long distance (~1 - 2 m) with a large assimilation fraction in the core plasma. As a RE probe, NPPJ is a unique combination of fast response with trigger-to-delivery time of few milliseconds, large mass-velocity (>75 mg at several km/s) and deep injection into post-TQ central plasma. The Objectives of this Category #1 project (concept development) were as follows: 1: We investigated the essential basic physics aspects of creating a plasma with ~10 15 to 10 16 cm -3 boron nitride (BN) NP density suited for a pulsed power plasma gun acceleration to several km/s. We concluded that, for RE NPPJ probe, BN (diameter Ø10 to 100 nm NPs) are in all respects usable. 2: We advanced solutions to get BN NPPJ by adapting FAR-TECH’s technology for C 60 NPPJ. 3: We developed self-consistent models for RE current density j RE (R; t) evolution in the TQ aftermath, with fast and simultaneous increase of n e (R; t) and Z eff (R; t) > 1 upon the specific injection of C 60 (i.e. C ions) and BN NP (i.e. B and N ions), respectively. We showed that prompt post-TQ injection and high velocity are of essence in RE probe diagnostics and suppression. 4: We used the in-house HEM-2D code to simulate the C$_{60}^{q+}$ NPPJ transverse penetration through tokamak-level B-field (BT ~2 to 5 T) and distance (~1 to 2m), with fragmentation of C$_{60}^{q+}$ and developed the algorithm for BN Q+ NPPJ ablative sublimation of BN Q+ NP by the collisions with post-TQ plasma electrons. HEM-2D results indicated that fragmenting C$_{60}^{1+}$ NPPJ penetrates up to ~60 cm in 100 us when injecting at 1.6 ms after TQ and gradually released C 2 fragments and C ions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2025

The Impact of Alfvénic Shear Flow on Magnetic Reconnection and Turbulence

Magnetic reconnection is a fundamental and omnipresent energy conversion process in plasma physics. Novel observations of fields and particles from Parker Solar Probe (PSP) have shown the absence of reconnection in a large number of current sheets in the near-Sun solar wind. Using near-Sun observations from PSP encounters 4–11 (2020 January–2022 March), we investigate whether reconnection onset might be suppressed by velocity shear. We compare estimates of the tearing mode growth rate in the presence of shear flow for time periods identified as containing reconnecting current sheets versus nonreconnecting times, finding systematically larger growth rates for reconnection periods. Upon examination of the parameters associated with reconnection onset, we find that 85% of the reconnection events are embedded in slow, non-Alfvénic wind streams. We compare with fast, slow non-Alfvénic, and slow Alfvénic streams, finding that the growth rate is suppressed in highly Alfvénic fast and slow wind, and reconnection is not seen in these wind types, as would be expected from our theoretical expressions. These wind streams have strong Alfvénic flow shear, consistent with the idea of reconnection suppression by such flows. This could help explain the frequent absence of reconnection events in the highly Alfvénic, near-Sun solar wind observed by PSP. Finally, we find a steepening of both the trace and magnitude magnetic field spectra within reconnection periods in comparison to ambient wind. We tie this to the dynamics of relatively balanced turbulence within these reconnection periods and the potential generation of compressible fluctuations.

slow solar wind↗

NASA NTRS2004

Computational Simulation of Acoustic Modes in Rocket Combustors

A combination of computational fluid dynamic analysis and analytical solutions is being used to characterize the dominant modes in liquid rocket engines in conjunction with laboratory experiments. The analytical solutions are based on simplified geometries and flow conditions and are used for careful validation of the numerical formulation. The validated computational model is then extended to realistic geometries and flow conditions to test the effects of various parameters on chamber modes, to guide and interpret companion laboratory experiments in simplified combustors, and to scale the measurements to engine operating conditions. In turn, the experiments are used to validate and improve the model. The present paper gives an overview of the numerical and analytical techniques along with comparisons illustrating the accuracy of the computations as a function of grid resolution. A representative parametric study of the effect of combustor mean flow Mach number and combustor aspect ratio on the chamber modes is then presented for both transverse and longitudinal modes. The results show that higher mean flow Mach numbers drive the modes to lower frequencies. Estimates of transverse wave mechanics in a high aspect ratio combustor are then contrasted with longitudinal modes in a long and narrow combustor to provide understanding of potential experimental simulations.

Harper, Brent↗