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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Pore-scale simulation of drying in porous media using a hybrid lattice Boltzmann: pore network model

In this work, a hybrid method coupling a pseudo-potential lattice Boltzmann model (LBM) and a pore network model (PNM) to simulate drying in porous media is proposed. Based on the watershed method, the porous medium is firstly decomposed into pore regions. According to the liquid–vapor phase distribution at a given time, the pore regions are further divided into four pore types, namely two-phase pores where a liquid–vapor interface exists, buffer pores next to the two-phase pores, single-liquid and single-vapor phase pores. The pseudo-potential LBM is used in the two-phase and buffer pores to simulate liquid drying and track the movement of the interfaces, while the single-phase PNM simulations are conducted in the buffer and single-phase pores to simulate vapor or liquid flow. LBM and PNM are coupled in the buffer pores through exchange of boundary information. The hybrid method is applied to simulate liquid drying in a porous medium. The whole-domain LBM simulation is considered as the reference solution to validate the hybrid method. Liquid saturation variation during the drying process and detailed phase and pressure distributions obtained by the two methods match quite well, demonstrating the accuracy of the hybrid method. For the specific case studied, the hybrid method saves more than 60% computational time compared to the whole-domain LBM simulation. In addition, the speedup of the hybrid method becomes more significant for a larger computational domain. In summary, the hybrid method developed in this work combines the accuracy of LBM and the efficiency of PNM to simulate drying in porous media at pore scale and can lead to significant reduction of computation time, thus allowing the pore-scale consideration of drying in larger porous systems.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Integrating Characteristic Arctic Vegetation in a Land Surface Model Improves Representation of Carbon Dynamics Across a Tundra Landscape: Modeling Archive

This modeling archive is in support of the Next-Generation Ecosystem Experiments in the Arctic (NGEE Arctic) publication "Integrating Characteristic Arctic Vegetation in a Land Surface Model Improves Representation of Carbon Dynamics Across a Tundra Landscape", by Murphy et al. (2025). This archive contains model input files and outputs from landscape-scale simulations conducted using ELM, the land model component of the Department of Energy’s Energy Exascale Earth System Model (E3SM), at the Council NGEE Arctic field site (Council Road mile marker 71) on Alaska’s Seward Peninsula. Input data and model output from two sets of ELM simulations are provided. The first set of simulations were conducted with the two default ELM Arctic plant functional types (PFTs; broadleaf deciduous boreal shrub and a C3 grass) and the second set of simulations were conducted with a set of nine Arctic-specific PFTs including nonvascular mosses and lichens, graminoids, forbs, evergreen dwarf shrubs, three height classes of deciduous shrubs (dwarf, low, and low to tall), and deciduous alder shrubs (Sulman et al., 2021). Parameter names and major parameter changes in the Arctic-specific PFT configuration are described in Sulman et al. (2021) and archived in the Sulman et al. (2021) dataset (see below). Simulations were spatially explicit, covering an approximately 6.4X3.3 km domain at the Council site with a spatial resolution of 100 m for a total of 2,112 simulated grid cells under each ELM PFT configuration. The modeling archive contains meteorological forcing (seven *.nc files and one *.txt file), a domain definition file (one *.nc files), land surface configuration files (two *.nc files), parameter files (two *.nc files), annual ELM output files spanning 1980-2014 (68 *.nc files), and a User’s Guide (*pdf file). Additional information on the provided files is in the “Modeling Archive Contents” section of the User’s Guide. Model outputs are aggregated to the column scale (i.e. PFT-specific outputs are not provided here).

Murphy, Bailey [ORNL] (ORCID:0000000203995221)↗
DOE OSTI2023

Radionuclide Transport Simulations Supporting Proposed Borehole Waste Disposal in Israel

A scientific collaboration between the U.S. and Israel is underway to assess the suitability of a potential site for subsurface radioactive waste disposal in the Negev Desert, Israel. The Negev Desert has several favorable attributes for geologic disposal, including an arid climate, a deep vadose zone, interlayered low-permeability lithologies, and carbonate rocks with high uranium-sorption potential. These features may provide a robust natural barrier to radionuclide migration. Geologic and laboratory characterization data from the Negev Desert are incorporated into multiphase flow and transport models, solved using PFLOTRAN, to aid in site characterization and risk analysis that will support decision-making for waste disposal in an intermediate-depth borehole design. The lithology with the greatest uranium sorption potential at the site is phosphorite. We use modeling to evaluate the ability of this layer to impact uranium transport around a proposed disposal borehole. The current objective of the simulations is focused on characterizing hypothetical leakage from waste canisters and subsequent uranium migration under three infiltration scenarios. Here, we describe a hydrogeologic model based on data from a local exploratory borehole and present results for uranium flow and transport simulations under varying infiltration scenarios. We find that under the current climate conditions, it is likely that uranium will remain in the near-field of the borehole for thousands of years. However, under a hypothesized extreme climate scenario representing an increase in infiltration by a factor of 300x above present-day values, uranium may break through the phosphorite layer and exit the base of the model domain (~200 m above the water table) within 1000 years. Simulation results have direct implications for the planning of nuclear waste disposal in the Negev Desert, and specifically in intermediate-depth boreholes.

58 GEOSCIENCES↗
DOE OSTI2023

Transboundary effects from idealized regional geoengineering

Regional geoengineering, by reflecting sunlight over a very limited spatial domain, might be considered as a means to target specific regional impacts of climate change. One of the obvious concerns raised by such approaches is the extent to which the resulting effects would be detectable well beyond the targeted region (e.g. in neighbouring countries). A few studies have explored this question for targeted regions that are still comparatively large. We consider idealized simulations with increased ocean albedo over relatively small domains; the Gulf of Mexico (0.23% of Earth's surface) and over the Australian Great Barrier Reef (0.07%), both with negligible global radiative forcing. Applied over these very small domains, the only statistically significant non-local changes we find are some limited reduction on summer precipitation in Florida in the Gulf of Mexico case (adjacent to the targeted region). The lack of transboundary effects suggests that governance needs for such targeted interventions are quite distinct from those for more global sunlight reflection.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Mineralogy, fabric and deformation domains in D" across the southwestern border of the African LLSVP

Recent advances in seismic anisotropy studies that jointly use reflections and shear wave splitting have proven to place tight constraints on the plausible anisotropic and deformation scenarios in the D" region. We apply this novel methodology to a large area of the D" region beneath the South Atlantic, in proximity to and within the African large low seismic velocity province (LLSVP). This area of the mantle is characterized by a transition from fast to slow seismic velocity anomalies and it is thought to be the location of deep-seated plumes responsible for hotspot volcanism. Attempting to probe mantle composition and deformation along the LLSVP borders may provide key information on mantle dynamics. By analysing seismic phases sampling this region, we detect a D" discontinuity over a large area beneath the South Atlantic, with inferred depth ranges ~170 to ~240 km above the core–mantle boundary. We find evidence for a D" reflector within the area of the LLSVP. Shear wave splitting observations suggest that anisotropy is present in this region of the mantle, in agreement with previous studies that partially sampled this region. We model the observations considering lattice- and shape-preferred orientation of materials expected in the D" region. A regional variation of mineralogy, phase transition boundaries, and deformation direction is required to explain the data. We infer two distinct domains of mineralogy and deformation: aligned post-perovskite outside the LLSVP and aligned bridgmanite within the LLSVP. Finally, the scenario depicted by this study agrees well with the current hypotheses for the composition of the LLSVP and with the prevalence of vertical deformation directions expected to occur along the LLSVPs borders.

58 GEOSCIENCES↗
DOE OSTI2021

Model estimates of dissolved organic carbon, runoff, snowmelt, and snow water equivalent from 1981-2010 across the western Arctic

This dataset contains estimates of dissolved organic carbon (DOC) yield (mg C m-2), runoff (mm day-1), snow water equivalent (SWE, mm day-1), and snowmelt (mm day-1) from a simulation of the Permafrost Water Balance Model (PWBM v4). The simulation effectively quantifies snowpack accumulation and melt, runoff, and DOC leaching, and broadly capture the seasonal cycle in DOC concentration and mass loadings. Daily air temperature, precipitation, and wind speed data from the Modern-Era Retrospective Analysis for Research and Applications (MERRA) were used for meteorological forcings. The model outputs are organized by grid and day of the month in gzipped ASCII text files contained within each archived ZIP file. No special software is required to work with these data. The basin and domain information files are also ASCII text. The gridded estimates are most useful for analyses of the spatial and temporal variations in terrestrial hydrology and leachate DOC concentrations and loadings across parts of the western Arctic. A manuscript describing the data and associated analysis has been accepted for publication in Journal of Geophysical Research - Biogeosciences (Rawlins et al., 2021).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Influence of atomic ordering and cerium doping on magnetostrictive Fe-Al alloys

Magnetostrictive iron-aluminum alloys can be a low-cost, mechanically stable alternative to iron-gallium and rare earth-iron alloys. The magnetostrictive performance of polycrystalline Fe-Al (alfenol) with 13–24 at. % Al was investigated, studying the role of compositional variation and thermal history. It was found that rapid cooling enhances the magnetostrictive response, and peak magnetostriction was found in Fe 78 Al 22 by high temperature annealing followed by quenching. Synchrotron diffraction enabled a direct correlation of magnetostrictive behavior and the transition from short-range order to long-range ordered cluster domains in the material which can be suppressed by rapid cooling. Following recent success of doping Fe-Ga with rare earth elements, we investigated the influence of Ce doping on improving magnetostriction and found that Fe-Al shows negligible solubility for cerium, inhibiting potential magnetostriction enhancement. In conclusion, our results illustrate the complex interplay between phase stability, ordering, and optimized magnetostrictive response.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Anomalous Transport in Three-Dimensional Discrete Fracture Networks: Interplay Between Aperture Heterogeneity and Injection Modes

In this work, we study how the interplay between fracture aperture heterogeneity and tracer injection mode controls fluid flow and tracer transport in three-dimensional (3D) discrete fracture networks (DFNs). The direct 3-D DFN simulations show that tracer injection mode has substantial effects on tracer spreading across all levels of aperture heterogeneity. The key controlling factor for effective transport is the initial Lagrangian velocity distribution, which is determined by the interplay between injection mode and aperture heterogeneity. The fundamental difference between initial Lagrangian velocity distribution and domain-scale Eulerian velocity distribution plays a vital role in determining anomalous transport. We effectively capture the observed anomalous transport using an upscaled transport model that incorporates initial velocity distribution, stationary velocity distribution, velocity correlation length, and average advective tortuosity. With the upscaled transport model, we accurately capture the evolution of Lagrangian velocity distribution and predict longitudinal spreading in 3-D DFN.

58 GEOSCIENCES↗
DOE OSTI2025

How initial conditions-, structural-, and parameter-based model uncertainty interact and influence predictions in permafrost ecosystems: Modeling Archive

This dataset contains model output and input data, as well as source code examples for the Terrestrial Ecosystem Model with the Dynamic Vegetation Model and Dynamic Organic Soil (DVM-DOS-TEM) for the field sites Imnavait creek and the Bonanza creek Long Term Ecological Research Network (LTER). The data covers simulations from the last glacial maximum (LGM) until 2100 for a selection of paleo scenarios, setting the mean temperature of the LGM up to 10°C lower than pre-industrial conditions. The model structure was modulated to represent various model versions, and this dataset contains the relevant changes in the source code. The raw output data, the processed statistical data, the setup and processing scripts as well as parameter value distribution files from a parameter sensitivity analysis are included as well. Model outputs include active layer depth, organic soil carbon, soil layer depths, gross primary productivity (GPP) with and without nitrogen limitation, net primary productivity (NPP), soil liquid water content, heterotrophic, maintenance, and growth respiration, soil temperature, and vegetation carbon (*.nc files). The Next-Generation Ecosystem Experiments in the Arctic (NGEE Arctic) project is a research effort to reduce uncertainty in the Department of Energy’s Energy Exascale Earth System Model (E3SM) by developing a predictive understanding of Arctic tundra ecosystems underlain by permafrost and to quantify feedbacks from the Arctic tundra to the Earth system. NGEE Arctic is supported by the Department of Energy's Office of Biological and Environmental Research.Over Phases 1–3, observations made by the NGEE Arctic team across a gradient of permafrost landscapes in Arctic Alaska improved the representation of tundra processes in the land surface component of E3SM (the E3SM Land Model, ELM). Model improvements emphasized unique aspects of permafrost environments and explored reductions in model complexity while retaining predictive power. The Arctic-informed ELM developed by NGEE Arctic has been used to make novel predictions on processes ranging from permafrost thaw to soil biogeochemical cycling to Earth system feedbacks associated with the unique characteristics of tundra plants. In Phase 4, the NGEE Arctic team is evaluating our new predictive understanding under novel conditions across the Arctic domain. In collaboration with partners at long-term pan-Arctic research sites we are examining whether an Arctic-informed ELM can faithfully simulate interactions among surface and subsurface processes at site, regional, and pan-Arctic scales. In turn, we are using variety of tools to dynamically extend and evaluate ELM inference, with an emphasis on data synthesis and pan-Arctic model evaluation, reintegration of code with an evolving E3SM, scaling across heterogeneous Arctic landscapes, and the appropriate representation of the impacts of increasingly frequent Arctic disturbances.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Structural and Optical Properties of High Entropy (La,Lu,Y,Gd,Ce)AlO 3 Perovskite Thin Films

Mixtures of Ce-doped rare-earth aluminum perovskites are drawing a significant amount of attention as potential scintillating devices. However, the synthesis of complex perovskite systems leads to many challenges. Designing the A-site cations with an equiatomic ratio allows for the stabilization of a single-crystal phase driven by an entropic regime. This work describes the synthesis of a highly epitaxial thin film of configurationally disordered rare-earth aluminum perovskite oxide (La 0.2 Lu 0.2 Y 0.2 Gd 0.2 Ce 0.2 )AlO 3 and characterizes the structural and optical properties. The thin films exhibit three equivalent epitaxial domains having an orthorhombic structure resulting from monoclinic distortion of the perovskite cubic cell. An excitation of 286.5 nm from Gd 3+ and energy transfer to Ce 3+ with 405 nm emission are observed, which represents the potential for high-energy conversion. These experimental results also offer the pathway to tunable optical properties of high-entropy rare-earth epitaxial perovskite films for a range of applications.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Site-level Foliar C, N, delta13C data from samples collected during field survey associated with NEON AOP survey, East River, CO 2018

Carbon (C) and nitrogen (N) weight percent concentrations were obtained from the bulk foliar samples collected across East River, Washington Gulch, Slate River, and Coal Creek watersheds in Gunnison, Colorado during the summer of 2018. These samples were collected from sun-lit leaves of meadow, shrub, and tree vegetation types within 72 hours of the National Ecological Observatory Network Airborne Observation Platform (NEON AOP) hyperspectral survey. These samples were dried and then run on an elemental analyzer coupled to a mass spectrometer for C and N concentrations and delta13C. The intention of these data were to provide ground truth data to develop foliar nutrient models across the imaging spectroscopy domain. Additional associated site metadata and vegetation fractional cover information can be found in the associated data releases (DOI: 10.15485/1618130). Here we provide site level C, N, and delta 13C data in the CN_Results_Foliar.csv. All of these samples were also registered with IGSN codes, and the details from that registration with metadata for the samples is included in foliar_sample_igsn_metadata.csv.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Recent Progress on Numerical Modeling for Microgravity Electric Field Flames: Preprint

This paper presents the recent progress on the NASA Physical Science Informatics (PSI) project PeleLM CFD of Ion Driven Winds from Diffusion Flames in simulating the E-FIELD Flames microgravity results. The focus of this project is to comprehensively simulate the behavior of a small diffusion flame under the influence of an externally applied electric field in zero-gravity. To date, the capability of accurately simulating electric field flames has eluded researchers because the system exhibits dramatic ranges of coupled temporal and spatial scales. Moreover, in earth gravity the hot combustion products are subject to buoyancy effects that are difficult to isolate from those generated by the electric field. This work is an implementation in an existing powerful simulation framework (PeleLM) for this problem using PeleLMeX in order to validate the model and investigate the complex coupled system. The current effort includes establishing the domain of a diffusion coflow burner, examining the boundary conditions, flame geometry and ignition with gravitational forces and also with an electric field applied. A detailed model is used that includes the chemistry of charged ions and chemiluminescent flame intermediates to capture any feedback between ion-driven convection and combustion behavior, and to allow quantitative comparisons with experimental measurements.

coflow flames↗
DOE OSTI2025

Model data for a watershed-scale study in the Portage River Basin (OH) examining the effects of subsurface drainage on the hydrologic response of an agricultural watershed.

This study builds on Rathore et al. (2024, WRR) and investigates the role of artificial tile-drainage on various aspects of watershed hydrological response, with a particular focus on peakflow. The model-data for the original modeling-focused paper (Rathore et al., 2024, WRR) is archived at Rathore et al. (2024, ESS-DIVE). Hence, this model-data archive provides scripts that are specific to this study that includes model updates, processing and analysis scripts. For details and models files of original model, readers are referred to Rathore et al. (2024, ESS-DIVE). The key difference between the model configuration in this study and Rathore et al. (2024, WRR) is that the tile drains are applied to the entire domain, to study the impact of tile-drains on different aspects of hydrological response. Additional scenario considering intensified precipitation after a dry period was also simulated. The Watershed Workflow package is implemented in Python3. The Jupyter notebooks can be executed through multiple open-source tools, for example, Anaconda Jupyter Lab, VS Studio Code, etc. Other data files include CSV and HDF5 files, which can be read through Python scripts.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Removing solar artifacts from Geostationary Lightning Mapper data to document lightning extremes

Here, we compare the performance of three different filters that identify solar artifacts in the Geostationary Lightning Mapper (GLM) data. These filters differ in their complexity and intended use. We use the most appropriate filters to document the severity of GLM solar contamination and to compute the frequency of extreme Americas lightning. Solar artifacts occur at an average rate of one every ~8 min. Due to their continuous emissions across a portion of the GLM CCD array, these events disproportionately contribute to the GLM event and group rates. Up to 40% of all events recorded between 10:00 and 12:00 local time during 2018 were solar artifacts. The frequency-domain solar filter also reveals a carrier wave at 50 to 60 Hz in some lightning flashes and solar episodes that appears to be anthropogenic in origin. Removing the relatively frequent solar artifact cases reveals rare cases of extreme lightning flashes. Exceptional flashes on the order of 500+ km in length and 10+ s in duration only occur a few times per year and are produced by storms that are predisposed for exceptional lightning rather than as single random occurrences.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Connect the Dots: In Situ 4-D Seismic Monitoring of CO 2 Storage With Spatio-Temporal CNNs

4-D seismic imaging has been widely used in CO 2 sequestration projects to monitor the fluid flow in the volumetric subsurface region that is not sampled by wells. Ideally, real-time monitoring and near-future forecasting would provide site operators with great insights to understand the dynamics of the subsurface reservoir and assess any potential risks. However, due to obstacles such as high deployment cost, availability of acquisition equipment, exclusion zones around surface structures, only very sparse seismic imaging data can be obtained during monitoring. That leads to an unavoidable and growing knowledge gap over time. The operator needs to understand the fluid flow throughout the project lifetime and the seismic data are only available at a limited number of times. This is insufficient for understanding reservoir behavior. To overcome those challenges, we have developed spatio-temporal neural-network-based models that can produce high-fidelity interpolated or extrapolated images effectively and efficiently. Specifically, our models are built on an autoencoder, and incorporate the long short-term memory (LSTM) structure with a new loss function regularized by optical flow. We validate the performance of our models using real 4-D post-stack seismic imaging data acquired at the Sleipner CO 2 sequestration field. We employ two different strategies in evaluating our models. Numerically, we compare our models with different baseline approaches using classic pixel-based metrics. We also conduct a blind survey and collect a total of 20 responses from domain experts to evaluate the quality of data generated by our models. Finally, via both numerical and expert evaluation, we conclude that our models can produce high-quality 2-D/3-D seismic imaging data at a reasonable cost, offering the possibility of real-time monitoring or even near-future forecasting of the CO 2 storage reservoir.

4-D seismic imaging↗
DOE OSTI2023

Journey Over Destination: Differentiable Sensor Placement Enhances Generalization [Poster]

The challenge of reconstructing spatial fields that change over time from limited sensor data has been a focal point for many research studies. Various machine learning methods have been used in attempts to address this complex issue, including convolutional neural networks. All of the proposed methods share a common requirement that the user needs to manually determine the sensor positions. This requirement remains a limiting factor in the ongoing quest for efficient learning and accurate field reconstruction. This study aims to present a method that enables a model to optimize sensor positions via backpropagation, thereby facilitating the model’s exploration of the spatial domain and enhancing sensor positioning effectively. Indexing naturally incorporates discrete decisions. This operation is nondifferentiable which is a requirement for the application of gradient-based optimization methods. We showcased its effectiveness by training an attention-based neural network, which achieved top-tier performance on two separate datasets. To our knowledge, this represents the first fully end-to-end differentiable workflow for enhancing sensor placement within a neural network model.

58 GEOSCIENCES↗
DOE OSTI2021

Ultrafast measurements of the interfacial spin Seebeck effect in Au and rare-earth iron-garnet bilayers

We investigate picosecond spin-currents across Au/iron-garnet interfaces in response to ultrafast laser heating of the electrons in the Au film. In the picoseconds after optical heating, interfacial spin currents occur due to an interfacial temperature difference between electrons in the metal and magnons in the insulator. We report measurements of this interfacial longitudinal spin Seebeck effect between Au and rare-earth iron-garnet insulators, i.e. RE 3 Fe 5 O 12 , where RE is Y, Eu, Tb, Tm. By systematically varying the rare-earth element, we modify the total magnetic moment of the iron-garnet. We use time domain thermoreflectance (TDTR) measurements to characterize the thermal response of the bilayer to ultrafast optical heating. We use time-resolved magneto-optic Kerr effect (TR-MOKE) measurements of the Au layer to measure the time-evolution of spin accumulation in the Au film. Replacing Y with other rare-earths enhances the electron-magnon conductance G e-m at the Au iron-garnet interface by as much as a factor of three. The electron-magnon conductance does not follow the trend of either the total magnetization of the iron garnet or the magnetic moment of the rare-earth.

36 MATERIALS SCIENCE↗
DOE OSTI2026

A Scalable Reduced‐Order Model for the Steady Navier–Stokes Equations

Scaling up new scientific technologies from laboratory to industry often involves demonstrating performance on a larger scale. Computer simulations can accelerate design and predictions in the deployment process, though traditional numerical methods are computationally intractable even for intermediate pilot plant scales. Recently, the component reduced order modeling method has been developed to tackle this challenge by combining projection reduced order modeling and discontinuous Galerkin domain decomposition. However, while many scientific or engineering applications involve nonlinear physics, this method has only been demonstrated for various linear systems. In this work, the component reduced order modeling method is extended to steady Navier–Stokes flow, with application to general nonlinear physics in view. The large‐scale, global domain is decomposed into a combination of small‐scale unit component. Linear subspaces for flow velocity and pressure are identified via proper orthogonal decomposition over sample snapshots collected from each small‐scale unit component. Velocity bases are augmented with a pressure supremizer to satisfy the inf–sup condition for stable pressure prediction. Two different nonlinear reduced order modeling methods are employed and compared for efficient evaluation of nonlinear advection: A third‐order tensor projection operator and the empirical quadrature procedure. The proposed method is demonstrated on the flow over arrays of five different unit objects, achieving a 23‐fold speedup with less than 4% relative error in domains up to 256 times larger than the unit components. Furthermore, a numerical experiment with the pressure supremizer strongly indicates the need for a supremizer for stable pressure prediction. A comparison between the tensorial approach and the empirical quadrature procedure revealed a slight advantage of the empirical quadrature procedure. The framework is compared with an alternating Schwarz‐based reduced‐order approach, demonstrating improved efficiency and robustness for the DG‐based global solver while retaining flexibility for sub‐scale iterative solvers. The method is further extended to a coupled advection–diffusion and Navier–Stokes system, illustrating its applicability to multi‐physics problems and its potential for more general, inter‐coupled nonlinear systems.

42 ENGINEERING↗