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DOE OSTI2025

Baseflow Identification via Explainable AI With Kolmogorov‐Arnold Networks

Abstract Hydrological models often involve constitutive laws that may not be optimal in every application. We propose to replace such laws with the Kolmogorov‐Arnold networks (KANs), a class of neural networks designed to identify symbolic expressions. We demonstrate KAN's potential on the problem of baseflow identification, a notoriously challenging task plagued by significant uncertainty. KAN‐derived functional dependencies of the baseflow components on the aridity index outperform their original counterparts; they demonstrate that water availability, rather than potential evapotranspiration, drives baseflow by constraining actual evapotranspiration under arid conditions. On a test set, they increase the Nash‐Sutcliffe efficiency (NSE) by 65%, decrease the root mean squared error by 29%, and increase the Kling‐Gupta efficiency by 34%. This superior performance is achieved while reducing the number of fitting parameters from three to two. Next, we use data from 378 catchments across the continental United States to refine the water‐balance equation at the mean‐annual scale. The KAN‐derived equations based on the refined water balance outperform both the current aridity index model, with up to a 105% increase in NSE, and the KAN‐derived equations based on the original water balance. While the performance of our model and tree‐based machine learning methods is similar, KANs offer the advantage of simplicity and transparency and require no specific software or computational tools. This case study focuses on the aridity index formulation, but the approach is flexible and transferable to other hydrological processes. Plain Language Summary Equations used in hydrologic model are often suboptimal, resulting in reduced prediction accuracy and efficiency. We implemented Kolmogorov‐Arnold networks (KAN), a machine learning algorithm for deriving symbolic formulations, to estimate groundwater recharge and showed that it outperforms an existing state‐of‐the‐art semi‐empirical formulation. In hydrology, Nash‐Sutcliffe efficiency (NSE), root mean squared error (RMSE), and Kling‐Gupta efficiency (KGE) are commonly used to evaluate model performance. Higher NSE and KGE values indicate better performance, while lower RMSE values are preferable. Our results show that NSE increased by 71%, RMSE decreased by 32%, and KGE improved by 25%. In addition, KAN identifies an optimal functional form and can be used to derive new analytical formulas using the prior knowledge. The KAN‐inspired equation outperformed the original formulation and reduced the fitting parameters. Furthermore, we refined the water‐balance equation at the mean‐annual scale and showed that, based on the new water‐balance equation, KAN can derive new formulations that are superior to the original aridity index formulations (up to 105% increase in NSE) and KAN‐derived equations based on the original water balance. These findings highlight the significant potential of KAN to advance the scientific understanding of a wide range of hydrologic processes. Key Points Kolmogorov‐Arnold networks (KANs) enhance interpretability of machine‐learned hydrological models KAN‐derived symbolic formulations outperform state‐of‐the‐art semi‐empirical aridity indices KAN‐identified functional form yields an analytical index with fewer fitting parameters and improved performance

baseflow↗

NASA NTRS2018

Solar Wind Implantation Into the Lunar Regolith: Monte Carlo Simulations of H Retention in a Surface With Defects and the H2 Exosphere

The solar wind implants protons into the top 20–30 nm of lunar regolith grains, and the implanted hydrogen will diffuse out of the regolith but also interact with oxygen in the regolith oxides. We apply a statistical approach to estimate the diffusion of hydrogen in the regolith hindered by forming temporary bonds with regolith oxygen atoms. A Monte Carlo simulation was used to track the temporal evolution of bound OH surface content and the H2 exosphere. The model results are consistent with the interpretation of the Chandrayaan‐1 M3 observations of infrared absorption spectra by surface hydroxyls as discussed in Li and Milliken (2017, https://doi.org/10.1126/sciadv.1701471). The model reproduced the latitudinal concentration of OH by using a Gaussian energy distribution of f(U(sub 0) = 0.5 eV, U(sub W) = 0.078–0.1 eV) to characterize the activation energy barrier to the diffusion of hydrogen in space weathered regolith. In addition, the model results of the exospheric content of H2 are consistent with observations by the Lyman Alpha Mapping Project on the Lunar Reconnaissance Orbiter. Therefore, we provide support for hydroxyl formation by chemically trapped solar wind protons.

Tucker, O. J.↗

NASA NTRS2018

Solar Wind Implantation Into the Lunar Regolith: Monte Carlo Simulations of H Retention in a Surface With Defects and the H2 Exosphere

The solar wind implants protons into the top 20–30 nm of lunar regolith grains, and the implanted hydrogen will diffuse out of the regolith but also interact with oxygen in the regolith oxides. We apply a statistical approach to estimate the diffusion of hydrogen in the regolith hindered by forming temporary bonds with regolith oxygen atoms. A Monte Carlo simulation was used to track the temporal evolution of bound OH surface content and the H2 exosphere. The model results are consistent with the interpretation of the Chandrayaan‐1 M3 observations of infrared absorption spectra by surface hydroxyls as discussed in Li and Milliken (2017, https://doi.org/10.1126/sciadv.1701471). The model reproduced the latitudinal concentration of OH by using a Gaussian energy distribution of f(U0 = 0.5 eV, UW = 0.078–0.1 eV) to characterize the activation energy barrier to the diffusion of hydrogen in space weathered regolith. In addition, the model results of the exospheric content of H2 are consistent with observations by the Lyman Alpha Mapping Project on the Lunar Reconnaissance Orbiter. Therefore, we provide support for hydroxyl formation by chemically trapped solar wind protons.

O J Tucker↗

NASA NTRS2022

KMT-2021-BLG-0912Lb: A Microlensing Super Earth Around A K-Type Star

Aims . The light curve of the microlensing event KMT-2021-BLG-0912 exhibits a very short anomaly relative to a single-lens single-source form. We investigate the light curve for the purpose of identifying the origin of the anomaly. Methods . We model the light curve under various interpretations. From this, we find four solutions, in which three solutions are found under the assumption that the lens is composed of two masses (2L1S models), and the other solution is found under the assumption that the source is comprised of binary stars (1L2S model). The 1L2S model is ruled out based on the contradiction that the faint source companion is bigger than its primary, and one of the 2L1S solutions is excluded from the combination of the poorer fit, blending constraint, and lower overall probability, leaving two surviving solutions with the planet/host mass ratios of q ∼ 2.8 × 10 −5 and ∼1.1 × 10 −5 . A subtle central deviation supports the possibility of a tertiary lens component, either a binary companion to the host with a very large or small separation, or a second planet lying near the Einstein ring, but it is difficult to claim a secure detection due to the marginal improvement of the fit, lack of consistency among different data sets, and difficulty in uniquely specifying the nature of the tertiary component. Results . With the observables of the event, it is estimated that the masses of the planet and host are ∼(6.9 M ⊕ , 0.75 M ⊙ ) according to one solution and ∼(2.8 M ⊕ , 0.80 M ⊙ ) according to the other, indicating that the planet is a super Earth around a K-type star, regardless of the solution. The fact that 16 (including the one reported in this work) out of 19 microlensing planets with M ≲ 10 M ⊕ were detected during the last 6 yr nicely demonstrates the importance of high-cadence global surveys in detecting very low-mass planets.

gravitational lensing↗

DOE OSTI2023

Measurements and computational analysis of the natural decay of 176 Lu

Background: Mainly because of its long half-life and despite its scientific relevance, spectroscopic measurements of 176 Lu forbidden β decays are very limited and lack formulation of shape factors. A direct precise measurement of its Q value is also presently unreported. In addition, the description of forbidden decays provides interesting challenges for nuclear theory. The comparison of precise experimental results with theoretical calculations for these decays can help to test underlying models and can aid the interpretation of data from other experiments. Purpose: Perform the first precision measurements of 176 Lu β-decay spectra and attempt the observation of its electron capture decays, as well as perform the first precision direct measurement of the 176 Lu β-decay Q value. Compare the shape of the precisely determined experimental β spectra to theoretical calculations, and compare the end point energy to that obtained from an independent Q value measurement. Method: Here, the 176 Lu β-decay spectra measurements and the search for electron capture decays were performed with an experimental setup that employed lutetium-containing scintillator crystals and a NaI(Tl) spectrometer for coincidence counting. The β decay Q value was determined via high-precision Penning trap mass spectrometry (PTMS) with the LEBIT facility at the National Superconducting Cyclotron Laboratory. The β-spectrum calculations were performed within the Fermi theory formalism with nuclear structure effects calculated using a shell model approach. Results: Both β transitions of 176 Lu were experimentally observed and corresponding shape factors formulated in their entire energy ranges. The search for electron capture decay branches led to an experimental upper limit of 6.3×10 –6 relative to its β decays. The 176 Lu β-decay and electron capture Q values were measured using PTMS to be 1193.0(6) and 108.9(8) keV, respectively. This enabled precise β end point energies of 596.2(6) and 195.3(6) keV to be determined for the primary and secondary β decays, respectively. The conserved vector current hypothesis was applied to calculate the relativistic vector matrix elements. The β-spectrum shape was shown to significantly depend on the Coulomb displacement energy and on the value of the axial vector coupling constant gA, which was extracted according to different assumptions. Conclusion: The implemented self-scintillation method has provided unmatched observations of 176 Lu, independently validated by the first direct measurements of its β-decay Q value by Penning trap mass spectrometry. Theoretical study of the main β transition led to the extraction of very different effective gA and log10f values, showing that a high-precision description of this transition would require a realistic nuclear structure with nucleus deformation.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

NASA NTRS2021

KMT-2021-BLG-0322: Severe Degeneracy Between Triple-lens and Higher-order Binary-lens Interpretations

We investigate the microlensing event KMT-2021-BLG-0322, for which the light curve exhibits three distinctive sets of caustic-crossing features. It is found that the overall features of the light curve are approximately described by a binary-lens (2L1S) model, but the model leaves substantial residuals. We test various interpretations with the aim of explaining the residuals. Methods. We find that the residuals can be explained either by considering a nonrectilinear lens-source motion caused by the microlens-parallax and lens-orbital effects or by adding a low-mass companion to the binary lens (3L1S model). The degeneracy between the higher-order 2L1S model and the 3L1S model is very severe, making it difficult to single out a correct solution based on the photometric data. This degeneracy was known before for two previous events (MACHO-97-BLG-41 and OGLE-2013-BLG-0723),which led to the false detections of planets in binary systems, and thus the identification of the degeneracy for KMT-2021-BLG-0322illustrates that the degeneracy can be not only common but also very severe, emphasizing the need to check both interpretations of deviations from 2L1S models. Results. From the Bayesian analysis conducted with the measured lensing observables of the event timescale, angular Einstein radius, and microlens parallax, it was estimated that the binary lens components have masses(M1,M2)=(0.62+0.25−0.26M,0.07+0.03−0.03M), for both2L1S and 3L1S solutions, and the mass of the tertiary lens component according to the 3L1S solution isM3=6.40+2.64−2.78MJ.

Gravitational lensing: micro↗

NASA NTRS2002

Classification image analysis: estimation and statistical inference for two-alternative forced-choice experiments

We consider estimation and statistical hypothesis testing on classification images obtained from the two-alternative forced-choice experimental paradigm. We begin with a probabilistic model of task performance for simple forced-choice detection and discrimination tasks. Particular attention is paid to general linear filter models because these models lead to a direct interpretation of the classification image as an estimate of the filter weights. We then describe an estimation procedure for obtaining classification images from observer data. A number of statistical tests are presented for testing various hypotheses from classification images based on some more compact set of features derived from them. As an example of how the methods we describe can be used, we present a case study investigating detection of a Gaussian bump profile.

Non-NASA Center↗

DOE OSTI2018

Search for natural supersymmetry in events with top quark pairs and photons in pp collisions at $\sqrt{s} =$ 8 TeV

Results are presented from a search for natural gauge-mediated supersymmetry (SUSY) in a scenario in which the top squark is the lightest squark, the next-to-lightest SUSY particle is a bino-like neutralino, and the lightest SUSY particle is the gravitino. The strong production of top squark pairs can produce events with pairs of top quarks and neutralinos, with each bino-like neutralino decaying to a photon and a gravitino. The search is performed using a sample of pp collision data accumulated by the CMS experiment at $ \sqrt{s}=8 $ TeV, corresponding to an integrated luminosity of 19.7 fb$^{−1}$. The final state consists of a lepton (electron or muon), jets, and one or two photons. The imbalance in transverse momentum in the events is compared with the expected spectrum from standard model processes. No excess event yield is observed beyond the expected background, and the result is interpreted in the context of a general model of gauge-mediated SUSY breaking that leads to exclusion of top squark masses below 650–730 GeV.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2016

New constraints and discovery potential for Higgs to Higgs cascade decays through vectorlike leptons

One of the cleanest signatures of a heavy Higgs boson in models with vectorlike leptons is H→e ± 4 ℓ ∓ →hℓ + ℓ - which, in two Higgs doublet model type-II, can even be the dominant decay mode of heavy Higgses. Among the decay modes of the standard model like Higgs boson, h, we consider bb¯¯ and γγ as representative channels with sizable and negligible background, respectively. We obtained new model independent limits on production cross section for this process from recasting existing experimental searches and interpret them within the two Higgs doublet model. In addition, we show that these limits can be improved by about two orders of magnitude with appropriate selection cuts immediately with existing data sets. We also discuss expected sensitivities with integrated luminosity up to 3 ab -1 and present a brief overview of other channels.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

NASA NTRS2005

3 Lectures: "Lagrangian Models", "Numerical Transport Schemes", and "Chemical and Transport Models"

The topics for the three lectures for the Canadian Summer School are Lagrangian Models, numerical transport schemes, and chemical and transport models. In the first lecture I will explain the basic components of the Lagrangian model (a trajectory code and a photochemical code), the difficulties in using such a model (initialization) and show some applications in interpretation of aircraft and satellite data. If time permits I will show some results concerning inverse modeling which is being used to evaluate sources of tropospheric pollutants. In the second lecture I will discuss one of the core components of any grid point model, the numerical transport scheme. I will explain the basics of shock capturing schemes, and performance criteria. I will include an example of the importance of horizontal resolution to polar processes. We have learned from NASA's global modeling initiative that horizontal resolution matters for predictions of the future evolution of the ozone hole. The numerical scheme will be evaluated using performance metrics based on satellite observations of long-lived tracers. The final lecture will discuss the evolution of chemical transport models over the last decade. Some of the problems with assimilated winds will be demonstrated, using satellite data to evaluate the simulations.

Anne Douglass↗

NASA NTRS2015

Why Is Improvement of Earth System Models so Elusive? Challenges and Strategies from Dust Aerosol Modeling

Past decades have seen an accelerating increase in computing efficiency, while climate models are representing a rapidly widening set of physical processes. Yet simulations of some fundamental aspects of climate like precipitation or aerosol forcing remain highly uncertain and resistant to progress. Dust aerosol modeling of soil particles lofted by wind erosion has seen a similar conflict between increasing model sophistication and remaining uncertainty. Dust aerosols perturb the energy and water cycles by scattering radiation and acting as ice nuclei, while mediating atmospheric chemistry and marine photosynthesis (and thus the carbon cycle). These effects take place across scales from the dimensions of an ice crystal to the planetary-scale circulation that disperses dust far downwind of its parent soil. Representing this range leads to several modeling challenges. Should we limit complexity in our model, which consumes computer resources and inhibits interpretation? How do we decide if a process involving dust is worthy of inclusion within our model? Can we identify a minimal representation of a complex process that is efficient yet retains the physics relevant to climate? Answering these questions about the appropriate degree of representation is guided by model evaluation, which presents several more challenges. How do we proceed if the available observations do not directly constrain our process of interest? (This could result from competing processes that influence the observed variable and obscure the signature of our process of interest.) Examples will be presented from dust modeling, with lessons that might be more broadly applicable. The end result will either be clinical depression or there assuring promise of continued gainful employment as the community confronts these challenges.

Climate models↗

NASA NTRS2005

Lunar and Planetary Science XXXVI, Part 6

Contents include the following: A Model for Multiple Populations of Presolar Diamonds. Characterization of Martian North Polar Geologic Units Using Mars Odyssey THEMIS Data. Effect of Flow on the Internal Structure of the Martian North Polar Layered Deposits. Elemental Abundance Distributions in Basalt Clays and Meteorites: Is It a Biosignature? Early Results on the Saturn System from the Composite Infrared Spectrometer. NanoSIMS D/H Imaging of Isotopically Primitive Interplanetary Dust Particles. Presolar (Circumstellar and Interstellar) Phases in Renazzo: The Effects of Parent Body Processing. Catastrophic Disruption of Hydrated Targets: Implications for the Hydrated Asteroids and for the Production of Interplanetary Dust Particles. Chemical and Mineralogical Analyses of Particles from the Stratospheric Collections Coinciding with the 2002 Leonid Storm and the 2003 Comet Grigg-Skjellerup Trail Passage. An Analysis of the Solvus in the CaS-MnS System. ESA s SMART-1 Mission at the Moon: First Results, Status and Next Steps. Europa Analog Ice-splitting Measurements and Experiments with Ice-Hunveyor on the Frozen Balaton-Lake, Hungary. Chromium on Eros: Further Evidence of Ordinary Chondrite Composition. Dust Devil Tracks on Mars: Observation and Analysis from Orbit and the Surface. Spatial Variation of Methane and Other Trace Gases Detected on Mars: Interpretation with a General Circulation Model. Mars Water Ice and Carbon Dioxide Seasonal Polar Caps: GCM Modeling and Comparison with Mars Express Omega Observations. Component Separation of OMEGA Spectra with ICA. Clathrate Formation in the Near-Surface Environment of Titan. Space Weathering: A Proposed Laboratory Approach to Explaining the Sulfur Depletion on Eros. Sample Collection from Small Airless Bodies: Examination of Temperature Constraints for the TGIP. Sample Collector for the Hera Near-Earth Asteroid Sample Return Mission. A Rugged Miniature Mass-Spectrometer for Measuring Aqueous Geochemistry on Mars. Martian and Lunar Pyroxene Microstructures Studied by Single-Crystal X-Ray Diffraction.

Source record↗

DOE OSTI2024

FORESTR: Finding, Organizing, Representing, Explaining, Summarizing, and Thinning Random forests

Random forests have become popular models used for data driven predictions. As a result, random forests are currently used or being considered for high-consequence mission applications in national security, such as the prediction of yield from optical signals and malware detection. While random forests may provide accurate predictions, the complexity of the algorithm causes a lack of interpretability. Random forests are an ensemble of regression or decision trees. Individual regression and decision trees are interpretable, but ensembles are inherently difficult to interpret due to the compilation of many models. We aim to increase the interpretability of random forests by finding patterns in the ensemble of trees that can be used to “thin” (or remove) trees. As a starting point, in this report, we develop a new distance metric for quantifying the similarity between trees based on their topologies (i.e., shapes). We base the metric on a novel distance metric for graphs that is a proper mathematical distance, is invariant to transformations, has registration between graphs, and computes topological evolutions between graphs. We use the tree distance metric to compute tree statistics such as a “mean tree” and to identify clusters of trees. We apply the developed methodology to a toy dataset and a mission relevant product inspection dataset to demonstrate how the metric can provide insight into random forests. Furthermore, we discuss the limitations of the approach and ideas for future research into how the metric could be used as a thinning tool to develop less complex models.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Recent DIII-D progress toward validating models of tungsten erosion, re-deposition, and migration for application to next-step fusion devices

Abstract Fundamental mechanisms governing the erosion and prompt re-deposition of tungsten impurities in tokamak divertors are identified and analyzed to inform the lifetime of tungsten plasma-facing components in ITER and other future devices. Various experiments conducted at DIII-D to benchmark predictive models are presented, leveraging the DiMES removable sample exposure probe capability and the Metal Rings Campaign, in which toroidally symmetric rows of tungsten-coated tiles were installed in the DIII-D divertor. In tokamak divertors, the width of the electric sheath is of the order of the main ion Larmor radius, and a vast majority of sputtered tungsten impurities are typically ionized within the sheath. Therefore, W prompt redeposition is mainly governed by the ratio of the characteristic ionization mean-free path of neutral tungsten to the width of the sheath. In-situ monitoring of the prompt redeposition of tungsten impurities in divertors is demonstrated via the use of WII/WI line ratios and the ionizations/photon (S/XB) method in L-mode discharges. Even with this relatively limited set of emission measurements, net erosion measurements were found to be a consistent upper bound to an analytic scaling based on the ratio of the W ionization length, λ iz , and the width of the magnetic sheath rather than the ratio of λ iz and the W + gyro-radius. In the far-scrape-off layer (SOL) of the ITER divertor, however, it is calculated that the measurement of photon emissions associated with the ionization of tungsten impurities up to W 5 + may be required. Finally, W deposition patterns on DiMES collector probes, interpreted via DIVIMP-WallDYN modelling, reveal the key roles of progressive W erosion/re-deposition staps and E × B drifts in regulating long-range high-Z material migration.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2021

Machine learning with persistent homology and chemical word embeddings improves prediction accuracy and interpretability in metal-organic frameworks

Machine learning has emerged as a powerful approach in materials discovery. Its major challenge is selecting features that create interpretable representations of materials, useful across multiple prediction tasks. We introduce an end-to-end machine learning model that automatically generates descriptors that capture a complex representation of a material’s structure and chemistry. This approach builds on computational topology techniques (namely, persistent homology) and word embeddings from natural language processing. It automatically encapsulates geometric and chemical information directly from the material system. We demonstrate our approach on multiple nanoporous metal–organic framework datasets by predicting methane and carbon dioxide adsorption across different conditions. Our results show considerable improvement in both accuracy and transferability across targets compared to models constructed from the commonly-used, manually-curated features, consistently achieving an average 25–30% decrease in root-mean-squared-deviation and an average increase of 40–50% in R 2 scores. A key advantage of our approach is interpretability: Our model identifies the pores that correlate best to adsorption at different pressures, which contributes to understanding atomic-level structure–property relationships for materials design.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

A Swing of the Pendulum: The Chemodynamics of the Local Stellar Halo Indicate Contributions from Several Radial Merger Events

We find that the chemical abundances and dynamics of APOGEE and GALAH stars in the local stellar halo are inconsistent with a scenario in which the inner halo is primarily composed of debris from a single massive, ancient merger event, as has been proposed to explain the Gaia-Enceladus/Gaia Sausage (GSE) structure. The data contain trends of chemical composition with energy that are opposite to expectations for a single massive, ancient merger event, and multiple chemical evolution paths with distinct dynamics are present. We use a Bayesian Gaussian mixture model regression algorithm to characterize the local stellar halo, and find that the data are fit best by a model with four components. We interpret these components as the Virgo Radial Merger (VRM), Cronus, Nereus, and Thamnos; however, Nereus and Thamnos likely represent more than one accretion event because the chemical abundance distributions of their member stars contain many peaks. Although the Cronus and Thamnos components have different dynamics, their chemical abundances suggest they may be related. We show that the distinct low- and high-α halo populations from Nissen & Schuster are explained by VRM and Cronus stars, as well as some in situ stars. Because the local stellar halo contains multiple substructures, different popular methods of selecting GSE stars will actually select different mixtures of these substructures, which may change the apparent chemodynamic properties of the selected stars. We also find that the Splash stars in the Solar region are shifted to higher v $\phi$ and slightly lower [Fe/H] than previously reported.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2017

Instantiation of crystal plasticity simulations for micromechanical modelling with direct input from microstructural data collected at light sources

Novel non-destructive characterization techniques performed at light sources provide previously inaccessible 3-D mesoscopic information on the deformation of polycrystalline materials. One major difficulty for interpretation of these experiments through micromechanical modelling is the likelihood that processing and/or mounting the sample introduce residual stresses in the specimen. These stresses need to be incorporated into crystal plasticity formulations, for these models to operate directly from microstructural images and be predictive. To achieve this, the initial micromechanical state of each voxel needs to be specified. Here in this letter we present a method for incorporating grain-averaged residual stresses for instantiation of crystal plasticity simulations.

36 MATERIALS SCIENCE↗

NASA NTRS1988

Linear and nonlinear interpretation of CV-580 lightning data

Numerical models developed for the study of lightning strike data acquired by in-flight aircraft are applied to the data measured on the CV-580. The basic technique used is the three dimensional time domain finite difference solution of Maxwell's equations. Both linear and nonlinear models are used in the analysis. In the linear model, the lightning channel and the aircraft are assumed to form a linear time invariant system. A transfer function technique can then be used to study the response of the aircraft to a given lightning strike current. Conversely, the lightning current can be inferred from the measured response. In the nonlinear model, the conductivity of air in the vicinity of the aircraft is calculated and incorporated into the solution of the Maxwell's equations. The nonlinear model thus simulates corona formation and air breakdown. Results obtained from the models are in reasonable agreement with the measured data. This study provides another validation of the models and increases confidence that the models may be used to predict aircraft response to any general lightning strike.

Ng, Poh H.↗