Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “difference scaling”

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.

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

At least 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
NASA NTRS1987

Basic properties and variability

Giant and supergiant M, S, and C stars are discussed in this survey of research. Basic properties as determined by spectra, chemical composition, photometry, or variability type are discussed. Space motions and space distributions of cool giants are described. Distribution of these stars in our galaxy and those nearby is discussed. Mira variables in particular are surveyed with emphasis on the following topics: (1) phase lag phenomenon; (2) Mira light curves; (3) variations in color indices; (4) determination of multiple periods; (5) correlations between quantities such as period length, light-curve shape, infrared (IR) excess, and visible and IR color diagram; (6) semiregular (SR) variables and different time scales in SR light variations; (7) irregular variable Lb and Lc stars; (8) different time-scale light variations; (9) hydrogen-deficient carbon (HdC) stars, in particular RCB stars; and (10) irreversible changes and rapid evolution in red variable stars.

Querci, Francois R.↗
DOE OSTI2024

KETCHUP: Parameterizing of large-scale kinetic models using multiple datasets with different reference states

Large-scale kinetic models provide the computational means to dynamically link metabolic reaction fluxes to metabolite concentrations and enzyme levels while also conforming to substrate level regulation. However, the development of broadly applicable frameworks for efficiently and robustly parameterizing models remains a challenge. Challenges arise due to both the heterogeneity, paucity, and difficulty in obtaining flux and/or concentration data but also due to the computational difficulties of the underlying parameter identification problem. Both the computational demands for parameterization, degeneracy of obtained parameter solutions and interpretability of results has so far limited widespread adoption of large-scale kinetic models despite their potential. Herein, we introduce the Kinetic Estimation Tool Capturing Heterogeneous Datasets Using Pyomo (KETCHUP), a flexible parameter estimation tool that leverages a primal-dual interior-point algorithm to solve a nonlinear programming (NLP) problem that identifies a set of parameters capable of recapitulating the (non)steady-state fluxes and concentrations in wild-type and perturbed metabolic networks. KETCHUP is benchmarked against previously parameterized large-scale kinetic models demonstrating an at least an order of magnitude faster convergence than the tool K-FIT while at the same time attaining better data fits. Finally, this versatile toolbox accepts different kinetic descriptions, metabolic fluxes, enzyme levels and metabolite concentrations, under either steady-state or instationary conditions to enable robust kinetic model construction and parameterization. KETCHUP supports the SBML format and can be accessed at https://github.com/maranasgroup/KETCHUP.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Statistical Homogenization of Elastic and Fracture Properties of a Sample Selective Laser Melting Material

Selective laser melting (SLM) is an additive manufacturing technique commonly used in the rapid prototyping of components. The complexity of the SLM microstructure poses a unique challenge to deriving effective mechanical properties at different length scales. Representative volume elements (RVEs) are often used to homogenize the material properties of composites. Instead of RVEs, we use statistical volume elements (SVEs) to homogenize the elastic and fracture properties of the material. This relates the inherent variation of a material’s microstructure to the variation in its mechanical properties at different observation scales. The convergence to the RVE limit is examined from two perspectives: the stability of the mean value as the SVE size increases for the mean-based approach, and the tendency of the normalized variation in homogenized properties to zero as the SVE size increases for the variation-based approach. Fracture properties tend to make the RVE limit slower than do elastic properties from both perspectives. There are also differences between vertical (normal to printing plane) and horizontal (in-plane) properties. While the elastic properties tend to make the RVE limit faster for the horizontal direction, i.e., having a smaller variation and more stable mean value, the fracture properties exhibit the opposite effect. We attributed these differences to the geometry of the melt pools.

36 MATERIALS SCIENCE↗
DOE OSTI2021

A seamless multiscale operator neural network for inferring bubble dynamics

Modelling multiscale systems from nanoscale to macroscale requires the use of atomistic and continuum methods and, correspondingly, different computer codes. Here, we develop a seamless method based on DeepONet, which is a composite deep neural network (a branch and a trunk network) for regressing operators. In particular, we consider bubble growth dynamics, and we model tiny bubbles of initial size from 100 nm to 10 $\mathrm {\mu }\textrm {m}$ , modelled by the Rayleigh–Plesset equation in the continuum regime above 1 $\mathrm {\mu }\textrm {m}$ and the dissipative particle dynamics method for bubbles below 1 $\mathrm {\mu }\textrm {m}$ in the atomistic regime. After an offline training based on data from both regimes, DeepONet can make accurate predictions of bubble growth on-the-fly (within a fraction of a second) across four orders of magnitude difference in spatial scales and two orders of magnitude in temporal scales. The framework of DeepONet is general and can be used for unifying physical models of different scales in diverse multiscale applications.

Mechanics↗
DOE OSTI2024

A conservative discontinuous-Galerkin-in-time (DGiT) multirate time integration framework for interface-coupled problems with applications to solid–solid interaction and air–sea models

In this paper we extend the DGiT multirate framework, developed in Connors and Sockwell (2022) for scalar transmission problems, to a solid–solid interaction (SSI) problem involving two coupled elastic solids and a coupled air–sea model with the rotating, thermal shallow water equations. In so doing we aim to demonstrate the broad applicability of the mathematical theory and governing principles established in Connors and Sockwell (2022) to coupled problems characterized by subproblems evolving at different temporal scales. Further, multirate time integration algorithms employing different time steps, optimized for the dynamics of each subproblem, can significantly improve simulation efficiency for such coupled problems. However, development of multirate algorithms is a highly non-trivial task due to the coupling, which can impact accuracy, stability or other desired properties such as preservation of system invariants. DGiT provides a general template for multirate time integration that can achieve these properties. To elucidate the manner in which DGiT accomplishes this task, we fully detail each step in the application of the framework to the SSI and air–sea coupled problems. Numerical examples illustrate key properties of the resulting multirate schemes for both problems.

42 ENGINEERING↗
DOE OSTI2024

FORCE Update 2024

The Framework for Optimization of Resources and Economics (FORCE) tool suite is the U.S. Department of Energy’s Nuclear Integrated Energy Systems (IES) Program flagship tool suite for technoeconomic IES analysis of IES. This tool suite is useful for analysis designed to evaluate and improve the technoeconomics of energy production systems, particularly for systems including nuclear technology. In this report, we document the development activity for the FORCE tool suite to extend its capabilities as performed during fiscal year 2024. In addition to reliability and accessibility, capability is one of the three standards guiding the development of the FORCE tool suite and the software codes that are its constituent parts. Extending the capabilities of the FORCE tool suite allows analysis both within the IES program as well as industry, university, and laboratory partners to perform analysis with more accuracy, insight, and impactful narrative. Four areas of capability development were the focus of activity this year: economic parameter uncertainty quantification, multiresolution analysis, components-to-optimization workflow automation, and statespace construction workflows for real-time optimal control. In economic parameter uncertainty quantification, the ability of HERON to capture risk due to scenarios (weather and energy demand uncertainty) was expanded to also include uncertainties in financial parameters such as capital cost or operation and maintenance costs. By including these sources of uncertainty, which are sometimes very large compared with scenario uncertainty, HERON is better able to capture the risk posed by investment in various IES technology. Because of this, analysts can also consider the reduction in risks that can be realized by choice of some technologies. In multiresolution analysis, development activity extended on work completed previously. In fiscal year 2023, methods for decomposing time series signals, such as demand, solar and wind availability, and price profiles, were analyzed and down-selected to those most effective at splitting signals into different resolutions. These resolutions allow considering the influence of different energy demand and supply behaviors across different time scales. For example, energy demand might be divided into seasonal, weekly, and hourly profiles. In fiscal year 2024, this preliminary work was extended and implemented within the Risk Analysis Virtual Environment (RAVEN) risk and uncertainty analysis platform, which is used throughout the FORCE framework. This development of the “multi-resolution time series analysis” (MR-TSA) module in RAVEN allows training synthetic history generators on complex time series. These synthetic history generators can then be used in HERON for generating scenarios that represent possible market and weather scenarios that can be analyzed on different time scales. We envision completing this work in the future, implementing multiresolution dispatch optimization strategies that can make the most beneficial use of these stratified time histories. In components-to-optimization workflow development, workflows for translating user inputs of components into algorithms for algebraic optimization were selected and implemented. Similar algorithms within the Holistic Energy Resource Optimization Network (HERON) were separated from the main code base of HERON and gathered with the components-to-optimization workflows in the new Dispatch Optimization Variable Engine (DOVE) software library. This modularization allows FORCE users to analyze dispatch optimization and energy system duty cycles independently of HERON, which previously was a burdensome task. Additionally, these dispatch optimization algorithms, set up in an independent library, can now be used across all software applications within FORCE, especially including the real-time optimal control software Optimization of Real-time Capacity Allocation (ORCA). Allowing FORCE software to share dispatch optimization algorithms within a single library allows for improved software maintenance and reliability. In statespace characterization workflow development, alternative workflows for optimizing dispatch with additional technical accuracy was the focus, particularly to improve the real-time optimization decision making in ORCA. Using algorithms and workflows initially developed for the Feasible Actuator Range Modifier (FARM), workflows for determining the statespace representation of IES were identified and demonstrated. The resulting dispatch optimization required a more robust optimization algorithm than that originally used in HERON (and moved to DOVE), which required adding an alternate workflow to DOVE that can more accurately match the behavior of physical systems using a partial differential equation representation. In conclusion, capability developments in the FORCE tool suite in fiscal year 2024 have improved the ability of the FORCE tool suite to perform

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2026

Degradation science: Integrating modeling and experiments to predict localized corrosion processes (Annual Progress Report)

Additively manufactured (AM) eutectic high-entropy alloys (EHEAs), such as nano-lamellar AlCoCrFeNi 2.1 , have excellent strength, ductility, and wear resistance even at elevated temperatures, but their corrosion behavior in aggressive acids at different length scales remain poorly understood. This work investigates the corrosion behavior of laser powder bed–fused (L-PBF) AlCoCrFeNi 2.1 as a function of annealing temperatures, probing degradation mechanisms from nanoscopic to macroscopic length scales. The alloy is dual phase consisting of a ductile FCC L1 2 phase and a high-strength BCC B2 phase. Rapid solidification during L-PBF produces a far-from-equilibrium nano-lamellar structure with nearly homogeneous elemental distribution, which tends to evolve upon annealing toward Cr/Co/Fe-enriched FCC and Al/Ni-enriched B2. Three conditions were studied: as-printed, 600 °C/5 h, and 1000 °C/1 h, over which B2 lamellae coarsen, lamellar spacing increases, and elemental segregation becomes more prominent. Microstructure and chemistry were characterized by scanning electron microscopy (SEM) and energy-dispersive spectroscopy (EDS), while in-situ electrochemical atomic force microscopy (EC-AFM) was used to link early (<5 h) local dissolution to microstructure after exposure in sulfuric acid. EC-AFM highlights preferential dissolution of the BCC/B2 phase where the surrounding matrix is Cr-depleted and directly quantifies the dissolution rates within individual phases, tracks the transition from early nano-scale attack to partial repassivation, to correlate height differences with current and impedance responses. To monitor longer-term behavior (up to 96 h), ex-situ AFM, SEM, and confocal imaging were combined with conventional bulk electrochemical tests, bridging nanoscale observations to micro/meso-scale damage morphologies. At the meso-scale, the deepest dissolution channels align with the build-direction lamellae and melt-pool boundaries, indicating that printing directionality guides the propagation of these localized corrosion sites. Annealing modifies corrosion by restructuring BCC/FCC phase fractions, lamellar spacing, and Cr/Al segregation, thereby changing the cathode/anode ratio and passive film stability. The results clarify how as-printed and annealed nano-lamellar architectures differ in their susceptibility to selective dissolution; how elemental segregation competes with residual stresses along the build direction. With these insights, future work will use CALPHAD-guided alloy modification to stabilize higher Cr contents in the B2 phase while retaining a dominant FCC+B2/BCC microstructure, with the goal of designing mechanically robust, corrosion-resistant EHEAs for safety-critical applications to leverage the LLNL’s broader national and global security mission.

36 MATERIALS SCIENCE↗
NASA NTRS1984

Ocean waves and turbulence as observed with an adaptive coherent multifrequency radar

An adaptive coherent multifrequency radar system is developed for several applications. The velocity distribution (Doppler spectrum) and spectral intensity of 15 different irregularity scales (waves and turbulence) can be measured simultaneously. Changing the azimuth angle of the antennas at regular intervals, the directivity of the wave/turbulence pattern on the sea surface can also be studied. A series of measurements for different air/sea conditions are carried out from a coast based platform. Experiments in the Atlantic are also performed with the same equipment making use of the NASA Electra aircraft. The multifrequency radar allows the measurement of the velocity distribution (""coherent and incoherent component'') associated with 15 different ocean irregularity scales simultaneously in a directional manner. It is possible to study the different air/sea mechanisms in some degree of detail.

Gjessing, D. T.↗
NASA NTRS2021

Combining Satellite Data and Spatial Analysis to Assess the UHI Amplitude and Structure within Urban Areas: The Case of Moroccan Cities

Landsat-8 surface temperature and the European Space Agency land cover are used to assess the impact of land cover on the Urban Heat Island (UHI) and Urban Heat Sink (UHS). We analyzed five Moroccan cities selected for their different local climate, size, and typology during summer at three different spatial scales. The results show multiple causes defining the different forms and amplitudes of the UHI, namely: the ambient climate, the proximity to the sea, the presence of landscaped areas, and the color of building roofs and walls. Contrary to what was expected, the vegetation was not systematically an island of coolness, either because of its typology or its irrigation status. In the coastal cities of Tangier and Casablanca, UHIs around 20°C are observed on the seaside, whereas a UHS of up to 11°C is observed between the city center and the southern periphery of Casablanca. A moderate amplitude UHI of 7°C is formed in the mountainous city of Ifrane. For cities built in desert-like environments, well-defined UHSs between 9°C and 12°C are observed in Smara and Marrakech, respectively. At a finer scale, towns recorded lower temperatures than their immediate surroundings, which are attributed to evaporation from irrigated plants.

Laila El Ghazouani↗
DOE OSTI2024

Sustainable strategies to achieve industrial ethanol titers from different bioenergy feedstocks: scale-up approach for better ethanol yield

Hydrothermal pretreatment is a promising approach to lignocellulosic biomass processing for enzymatic hydrolysis and high-yield bioethanol fermentation, as it reduces downstream inhibitor content and the amount of toxic byproducts generated. In this paper, the ethanol yield and productivity of an engineered xylose-fermenting strain of Saccharomyces cerevisiae were tested on lignocellulosic hydrolysates produced with varying citrate buffer concentration, solid loading, supplemental nitrogen source, and feedstock of origin, and a semi-integrated bioprocess which integrates enzymatic hydrolysis and bioethanol fermentation was developed. The greatest ethanol yields (g p /g s ) of 0.490 ± 0.008, 0.460 ± 0.001, 0.420 ± 0.002 and 0.410 ± 0.002 were obtained from bioenergy sorghum (BES), Miscanthus × giganteus (MG), energy cane (EC), and oilcane (OC), respectively. In addition, an equivalent of 291 L, 253.54 L, 257.8 L, and 260.3 L of bioethanol were produced per ton of BES, MG, EC, and OC, respectively, by using urea as a nitrogen source in a bioreactor.

09 BIOMASS FUELS↗
NASA NTRS1989

Outputs of paired Gabor filters summed across the background frame of reference predict the direction of movement

A cortical neural network that computes the visibility of shifts in the direction of movement is proposed. The network computes: (1) the magnitude of the position difference between the test and background patterns, (2) localized contrast differences at different spatial scales analyzed by computing temporal gradients of the difference and sum of the outputs of paired even- and odd-symmetric bandpass filters convolved with the input pattern, and (3) using global processes that pool the output from paired even- and odd-symmetric simple and complex cells across the spatial extent of the background frame of reference the direction a test pattern moved relative to a textured background. Evidence that magnocellular pathways are used to discriminate the direction of movement is presented. Since magnocellular pathways are used to discriminate the direction of movement, this task is not affected by small pattern changes such as jitter, short presentations, blurring, and different background contrasts that result when the veiling illumination in a scene changes.

Lawton, Teri B.↗
NASA NTRS1992

Method and apparatus for predicting the direction of movement in machine vision

A computer-simulated cortical network is presented. The network is capable of computing the visibility of shifts in the direction of movement. Additionally, the network can compute the following: (1) the magnitude of the position difference between the test and background patterns; (2) localized contrast differences at different spatial scales analyzed by computing temporal gradients of the difference and sum of the outputs of paired even- and odd-symmetric bandpass filters convolved with the input pattern; and (3) the direction of a test pattern moved relative to a textured background. The direction of movement of an object in the field of view of a robotic vision system is detected in accordance with nonlinear Gabor function algorithms. The movement of objects relative to their background is used to infer the 3-dimensional structure and motion of object surfaces.

Lawton, Teri B.↗
NASA NTRS2009

Identifying Optimal Temporal Scale for the Correlation of AOD and Ground Measurements of PM2.5 to Improve the Model Performance in a Real-time Air Quality Estimation System

Aerosol optical depth (AOD), an indirect estimate of particle matter using satellite observations, has shown great promise in improving estimates of PM 2.5 air quality surface. Currently, few studies have been conducted to explore the optimal way to apply AOD data to improve the model accuracy of PM 2.5 surface estimation in a real-time air quality system. We believe that two major aspects may be worthy of consideration in that area: 1) the approach to integrate satellite measurements with ground measurements in the pollution estimation, and 2) identification of an optimal temporal scale to calculate the correlation of AOD and ground measurements. This paper is focused on the second aspect on the identifying the optimal temporal scale to correlate AOD with PM2.5. Five following different temporal scales were chosen to evaluate their impact on the model performance: 1) within the last 3 days, 2) within the last 10 days, 3) within the last 30 days, 4) within the last 90 days, and 5) the time period with the highest correlation in a year. The model performance is evaluated for its accuracy, bias, and errors based on the following selected statistics: the Mean Bias, the Normalized Mean Bias, the Root Mean Square Error, Normalized Mean Error, and the Index of Agreement. This research shows that the model with the temporal scale of within the last 30 days displays the best model performance in this study area using 2004 and 2005 data sets.

Li, Hui↗
NASA NTRS2013

Impacts of Disturbance History on Forest Carbon Stocks and Fluxes: Merging Satellite Disturbance Mapping with Forest Inventory Data in a Carbon Cycle Model Framework

Forest carbon stocks and fluxes are highly dynamic following stand-clearing disturbances from severe fire and harvest and this presents a significant challenge for continental carbon budget assessments. In this work we use forest inventory data to parameterize a carbon cycle model to represent post-disturbance carbon trajectories of carbon pools and fluxes for specific forest types growing in high and low site productivity class settings. We then apply these trajectories to landscapes and regions based on forest age distributions derived from either the FIA data or from Landsat time series stacks (1985-2006) for 54 representative scenes throughout most of the conterminous United States. We estimate the net carbon uptake in forests caused by post-disturbance growth and decomposition ("regrowth sink") for forested regions across the country. At the landscape scale, the prevailing condition of positive net ecosystem productivity (NEP) is in stark contrast to local patches with large sources, particularly in the west where fires and clear cuts create contiguous disturbed patches. At the continental scale, regional differences in disturbance rates reflect management patterns of high disturbance rates in the Southeastern and South Central states, and lower disturbance rates in the Northeast and Northern Lakes States. Despite low contemporary disturbance rates in the Northeast and Northern Lakes States (0.61 and 0.74% y(exp −1)), the regrowth sink there remains of moderate to large strength (88 and 57 g C m(exp −2) y(exp −1)) owing to the continued legacy from historical clearing. Large regrowth sinks are also found in the Southeast, South Central, and Pacific Southwest regions (85, 86, and 95 g C m(exp −2) y(exp −1)) where disturbance rates also tend to be higher (1.59, 1.38, and 0.93% y(exp −1)). Overall, the Landsat-derived disturbance rates are elevated relative to FIA-derived rates (1.19 versus 0.93% y(exp −1)) particularly for western regions. The differences only modestly adjust regional- and continental-scale carbon budgets, reducing NEP from forest regrowth by about 8%.

carbon↗
DOE OSTI2023

Characterizing Performance of Freshwater Wetland Methane Models Across Time Scales at FLUXNET-CH 4 Sites Using Wavelet Analyses

Process-based land surface models are important tools for estimating global wetland methane (CH 4 ) emissions and projecting their behavior across space and time. So far there are no performance assessments of model responses to drivers at multiple time scales. In this study, we apply wavelet analysis to identify the dominant time scales contributing to model uncertainty in the frequency domain. We evaluate seven wetland models at 23 eddy covariance tower sites. Our study first characterizes site-level patterns of freshwater wetland CH 4 fluxes (FCH 4 ) at different time scales. A Monte Carlo approach was developed to incorporate flux observation error to avoid misidentification of the time scales that dominate model error. Our results suggest that (a) significant model-observation disagreements are mainly at multi-day time scales (<15 days); (b) most of the models can capture the CH 4 variability at monthly and seasonal time scales (>32 days) for the boreal and Arctic tundra wetland sites but have significant bias in variability at seasonal time scales for temperate and tropical/subtropical sites; (c) model errors exhibit increasing power spectrum as time scale increases, indicating that biases at time scales <5 days could contribute to persistent systematic biases on longer time scales; and (d) differences in error pattern are related to model structure (e.g., proxy of CH 4 production). Our evaluation suggests the need to accurately replicate FCH 4 variability, especially at short time scales, in future wetland CH 4 model developments.

58 GEOSCIENCES↗
DOE OSTI2021

Universality class for loopless invasion percolation models and a percolation avalanche burst model for hydraulic fracturing

Invasion percolation is a model that was originally proposed to describe growing networks of fractures. In this work, we describe a loopless algorithm on random lattices, coupled with an avalanche-based model for bursts. The model reproduces the characteristic b-value seismicity and spatial distribution of bursts consistent with earthquakes resulting from hydraulic fracturing (“fracking”). We test models for both site invasion percolation and bond invasion percolation. These have differences on the scale of site and bond lengths l. But since the networks are characterized by their large-scale behavior, l << L, we find small differences between scaling exponents. Though data may not differentiate between models, our results suggest that both models belong to different universality classes.

58 GEOSCIENCES↗
DOE OSTI2024

Discoveries in Blast-Driven Turbulence of Astrophysical Relevance

The fluid mixing caused by variable-density instabilities is important in a wide variety of scenarios from ocean mixing and astrophysical phenomena to nuclear fusion techniques and atomic weapons. This thesis explores the mixing resulting from a specific instability known as the Blast Driven Instability (BDI). This work investigates the variable density mixing in an explosively driven environment due to the fluid instabilities at the material interfaces. Specifically, diverging Richtmyer-Meshkov (impulsive-acceleration environment) and Rayleigh-Taylor (variable-acceleration environment) instabilities (present in supernova and inertial confinement fusion) are studied using advanced high-speed diagnostics in carefully designed laboratory experiments. The BDI morphology is presented through a time development of Mie scattering images, and steps through the parameter space (varying density ratio and driver speed), highlighting the development of the structures that form during mixing. A scaling criterion is used to relate the two systems of vastly different spatiotemporal scales. Velocity fields in the BDI have been captured for the first time using the high temporal resolution PIV technique. Subsequent analysis of the dynamics of the instability from the velocity fields illustrates the distribution of kinetic energy, the transition to turbulence, and the characteristic growth of the instability are discussed. This study furthers understanding of how blast-driven instability pertains to supernova and inertial confinement fusion science. The morphology of the BDI has been characterized for the first time. This work steps through the parameter space covered in Mie scattering experiments, and how the different parameters contribute to development of structures and mixing. It also examines a scaling of the Atwood number for expanding predictive capabilities to other experimental conditions and simulations. The first collection of velocity fields acquired for the BDI are recorded, and subsequent analysis evaluating the distribution of kinetic energy throughout space and time for two density ratios from the overall parameter space, as well as the transition to turbulence, estimated from a Reynolds number calculated based on momentum mixing are all presented. This information is useful in advancing the development of models to predict physics of high energy density applications where experiments are not always readily available. This research has successfully demonstrated understanding for the time criteria defining regimes where the shock driven (Richtmyer-Meshkov instability) and the buoyancy driven (Rayleigh-Taylor instability) dominates through a parametric study of density variation (Atwood number) and driver speed (Mach number). All this furthers understanding of how the BDI pertains to SN and ICF.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Effects of wave damping and finite perpendicular scale on three-dimensional Alfvén wave parametric decay in low-beta plasmas

Shear Alfvén wave parametric decay instability (PDI) provides a potential path toward significant wave dissipation and plasma heating. However, fundamental questions regarding how PDI is excited in a realistic three-dimensional (3D) open system and how the finite perpendicular wave scale—as found in both laboratory and space plasmas—affects the excitation remain poorly understood. Here, we present the first 3D, open-boundary, hybrid kinetic-fluid simulations of kinetic Alfvén wave PDI in low-beta plasmas. Key findings are that the PDI excitation is strongly limited by the wave damping present, including electron–ion collisional damping (represented by a constant resistivity) and geometrical attenuation associated with the finite-scale Alfvén wave, and ion Landau damping of the child acoustic wave. The perpendicular wave scale alone, however, plays no discernible role: waves of different perpendicular scales exhibit similar instability excitation as long as the magnitude of the parallel ponderomotive force remains unchanged. These findings are corroborated by theoretical analysis and estimates. This new understanding of 3D kinetic Alfvén wave PDI physics is essential for laboratory study of the basic plasma process and may also aid future evaluation of the relevance/role of PDI in low-beta space plasma.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗