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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
NASA NTRS1999

Automated Development of Accurate Algorithms and Efficient Codes for Computational Aeroacoustics

The simulation of sound generation and propagation in three space dimensions with realistic aircraft components is a very large time dependent computation with fine details. Simulations in open domains with embedded objects require accurate and robust algorithms for propagation, for artificial inflow and outflow boundaries, and for the definition of geometrically complex objects. The development, implementation, and validation of methods for solving these demanding problems is being done to support the NASA pillar goals for reducing aircraft noise levels. Our goal is to provide algorithms which are sufficiently accurate and efficient to produce usable results rapidly enough to allow design engineers to study the effects on sound levels of design changes in propulsion systems, and in the integration of propulsion systems with airframes. There is a lack of design tools for these purposes at this time. Our technical approach to this problem combines the development of new, algorithms with the use of Mathematica and Unix utilities to automate the algorithm development, code implementation, and validation. We use explicit methods to ensure effective implementation by domain decomposition for SPMD parallel computing. There are several orders of magnitude difference in the computational efficiencies of the algorithms which we have considered. We currently have new artificial inflow and outflow boundary conditions that are stable, accurate, and unobtrusive, with implementations that match the accuracy and efficiency of the propagation methods. The artificial numerical boundary treatments have been proven to have solutions which converge to the full open domain problems, so that the error from the boundary treatments can be driven as low as is required. The purpose of this paper is to briefly present a method for developing highly accurate algorithms for computational aeroacoustics, the use of computer automation in this process, and a brief survey of the algorithms that have resulted from this work. A review of computational aeroacoustics has recently been given by Lele.

Goodrich, John W.↗
DOE OSTI2021

Linear and Nonlinear Solvers for Simulating Multiphase Flow within Large-Scale Engineered Subsurface Systems

Simulation of multiphase flow in the subsurface is well-known to be computationally challenging. While there have been many studies that have explored approaches to overcoming these challenges, they often utilize relatively simple case studies. In this paper, we focus on the unique numerical challenges posed by modeling large-scale engineered subsurface systems, characterized by discrete features embedded in a heterogeneous natural subsurface setting. The man-made features such as shafts, tunnels, and barriers often cause multiple challenges in modeling the domain for multiphase porous media flow. This flow scenario can have a wide range of applications such as nuclear waste repositories, enhanced recovery of a petroleum reservoir, geothermal engineering, and carbon sequestration. An example of these severe numerical challenges is the case of performance assessment (PA) for Waste Isolation Pilot Plant (WIPP), the only operating deep geological repository in the US, which simulates extreme material properties of bedded salt rock formation and extreme contrast due to open excavation next to the formation. The models have extremes not only of permeability and porosity but also of the constitutive models needed for multiphase flow; additionally, they have process models like salt creep closure reducing porosity over time, fracturing in clay and anhydrite interbeds of the bedded salt, gas generation from the waste materials, and unintentional human borehole intrusions in some scenarios. Numerical simulations require the solution of coupled systems of nonlinear PDEs; in our work, we use the open-source simulator PFLOTRAN which is based on Finite Volume discretization. The solution of the nonlinear equations requires use of the Newton-Raphson iteration at each time step, which entails the solution of the linearized Jacobian system at each iteration. The effects of all the processes (i.e., large number of unknowns, highly nonlinear constitutive relations, large contrasts in material properties in short distances) lead to an ill-conditioned Jacobian matrix that severely challenges traditional linear solver, i.e., stabilized biconjugate gradient with block Jacobi incomplete LU preconditioner (BCGS-ILU) leading to non-convergence for traditional Newton-Raphson nonlinear solver causing unacceptably long computation time for each model. This paper presents linear solvers such as constrained pressure residual (CPR) two-stage preconditioner with alternate-block-factorization (ABF) and quasi- implicit pressure and explicit saturation (QIMPES) decouplers and flexible generalized residual solver (FGMRES). The new general-purpose nonlinear solver, Newton trust-region dogleg Cauchy (NTRDC), is also introduced to resolve extreme nonlinearities in the models. We demonstrate the effectiveness of each method relative to the default BCGS-Newton solver. The two best cases had nearly 50 times speed-up and achieved completion of a simulation in 14 hours that never completed due to non-convergence with the default solver. We also investigate the strong scalability of each method and discuss some of the deficiencies found for Block Jacobi preconditioner using parallel domain decomposition, and node packing effects of modern processor architecture.

Preconditioner, Nonlinear, Porous media, Multiphas↗
DOE OSTI2022

Ladder symmetries of black holes. Implications for love numbers and no-hair theorems

It is well known that asymptotically flat black holes in general relativity have a vanishing static, conservative tidal response. Here, we show that this is a result of linearly realized symmetries governing static (spin 0,1,2) perturbations around black holes. The symmetries have a geometric origin: in the scalar case, they arise from the (E)AdS isometries of a dimensionally reduced black hole spacetime. Underlying the symmetries is a ladder structure which can be used to construct the full tower of solutions, and derive their general properties: (1) solutions that decay with radius spontaneously break the symmetries, and must diverge at the horizon; (2) solutions regular at the horizon respect the symmetries, and take the form of a finite polynomial that grows with radius. Taken together, these two properties imply that static response coefficients — and in particular Love numbers — vanish. Moreover, property (1) is consistent with the absence of black holes with linear (perturbative) hair. We also discuss the manifestation of these symmetries in the effective point particle description of a black hole, showing explicitly that for scalar probes the worldline couplings associated with a non-trivial tidal response and scalar hair must vanish in order for the symmetries to be preserved.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

DeepAndes: A Self-Supervised Vision Foundation Model for Multispectral Remote Sensing Imagery of the Andes

By mapping sites at large scales usingremotely sensed data, archaeologists can generate unique insights into long-term demographic trends, interregional social networks, and human adaptations in the past. Remote sensing surveys complement field-based approaches, and their reach can be especially great when combined with deep learning and computer vision techniques. However, conventional supervised deep learning methods face challenges in annotating fine-grained archaeological features at scale. In addition, while recent vision foundation models have shown remarkable success in learning large-scale remote sensing data with minimal annotations, most off-the-shelf solutions are designed for RGB images rather than multispectral satellite imagery, such as the eight-band data used in our study. In this article, we introduce DeepAndes, a transformer-based vision foundation model trained on three million multispectral satellite images, specifically tailored for Andean archaeology. DeepAndes incorporates a customized DINOv2 self-supervised learning algorithm optimized for eight-band multispectral imagery, marking the first foundation model designed explicitly for the Andes region. We evaluate its image understanding performance through imbalanced image classification, image instance retrieval, and pixel-level semantic segmentation tasks. Our experiments show that DeepAndes achieves superior F1 scores, mean average precision, and Dice scores in few-shot learning scenarios, significantly outperforming models trained from scratch or pretrained on smaller datasets. This underscores the effectiveness of large-scale self-supervised pretraining in archaeological remote sensing.

Guo, Junlin [Vanderbilt Univ., Nashville, TN (Unit↗
NASA NTRS1991

A semi-elliptic analysis for 2-D viscous flows through cascade configurations

A semielliptic formulation, termed the interacting parabolized Navier-Stokes (IPNS) formulation, is developed for the analysis of a class of subsonic viscous flows for which streamwise diffusion is negligible but which are significantly influenced by upstream interactions. A two-step alternating-direction-explicit numerical scheme is developed to solve the resulting governing equations efficiently. The quasi-linearization and discretization of the equations are carefully examined so that no artificial viscosity is added externally to the scheme. Various simple channel and cascade flow configurations are examined for several values of Re, thickness ratio and Mach number, in order to establish the applicability of the IPNS model for these flows. With this model, solutions to compressible as well as nearly incompressible flows are obtained without any modification either in the analysis or in the solution procedure.

Ramamurti, R.↗
NASA NTRS1994

Asymptotic domination of cold relativistic MHD winds by kinetic energy flux

We study the conditions which lead to the conversion of most Poynting flux into kinetic energy flux in cold, relativistic hydromagnetic winds. It is shown that plasma acceleration along a precisely radial flow is extremely inefficient due to the near cancellation of the toroidal magnetic pressure and tension forces. However, if the flux tubes in a flow diverge even slightly faster than radially, the fast magnetosonic point moves inward from infinity to a few times the light cylinder radius. Once the flow becomes supermagnetosonic, further divergence of the flux tubes beyond the fast point can accelerate the flow via the 'magnetic nozzle' effect, thereby further converting Poynting flux to kinetic energy flux. We show that the Grad-Shafranov equation admits a generic family of kinetic energy-dominated asymptotic wind solutions with finite total magnetic flux. The Poynting flux in these solutions vanishes logarithmically with distance. The way in which the flux surfaces are nested within the flow depends only on the ratio of angular velocity to poliodal 4-velocity as a function of magnetic flux. Radial variations in flow structure can be expressed in terms of a pressure boundary condition on the outermost flux surface, provided that no external toriodal field surrounds the flow. For a special case, we show explicitly how the flux surfaces merge gradually to their asymptotes. For flows confined by an external medium of pressure decreasing to zero at infinity we show that, depending on how fast the ambient pressure declines, the final flow state could be either a collimated jet or a wind that fills the entire space. We discuss the astrophysical implications of our results for jets from active galactic nuclei and for free pulsar winds such as that believed to power the Crab Nebula.

Begelman, Mitchell C.↗
DOE OSTI2021

Mechanistic Study of the Li–Air Battery with a Co 3 O 4 Cathode and Dimethyl Sulfoxide Electrolyte

The lithium–air battery, a powerful competitor to replace the traditional lithium-ion battery, has attracted increasing attention due to its extremely high theoretical energy density. However, its development is limited by the cathode and electrolyte properties, which should include high stability, conductivity, and electrocatalytic properties in oxygen-rich environments. Here, we employ a systematic first-principles study of Li–O 2 discharge and charge reactions on the Co 3 O 4 -based cathode with the assistance of dimethyl sulfoxide (DMSO) electrolyte. The structure, stability, and electronic properties of different surface reconstructions of the Co 3 O 4 (100) facet are investigated. In addition, the mechanisms and thermodynamic overpotentials of multi-step reactions between Li + /e – and O 2 are provided, where lithium suboxide products (Li 2 O 2 or Li 3 O 2 ) are formed on the different Co 3 O 4 (100) terminations. The solvation shell of Li + components in explicit DMSO solvent is investigated through ab initio molecular dynamics simulations. In general, we find that the Co 3 O 4 (100)-O (oxidized) surface is the most stable one under standard conditions, and the stable Li + solvation structure is found in a tetrahedral Li(DMSO) 4 + shell in the DMSO-based electrolyte. Moreover, in the system of the Co 3 O 4 (100)-O cathode and DMSO electrolyte, the solution model pathway is energetically favorable for the Li–O 2 discharge reaction. It provides a low constant overpotential of 0.17 V during a long-term discharging process, thus causing the final toroid Li 2 O 2 formation on the cathode. During the charging process, an overpotential of 0.36 V is required to rapidly decompose Li 2 O 2 .

25 ENERGY STORAGE↗
DOE OSTI2021

A multiresolution adaptive wavelet method for nonlinear partial differential equations

We report the multiscale complexity of modern problems in computational science and engineering can prohibit the use of traditional numerical methods in multi-dimensional simulations. Therefore, novel algorithms are required in these situations to solve partial differential equations (PDEs) with features evolving on a wide range of spatial and temporal scales. To meet these challenges, we present a multiresolution wavelet algorithm to solve PDEs with significant data compression and explicit error control. We discretize in space by projecting fields and spatial derivative operators onto wavelet basis functions. We provide error estimates for the wavelet representation of fields and their derivatives. Then, our estimates are used to construct a sparse multiresolution discretization which guarantees the prescribed accuracy. Additionally, we embed a predictor-corrector procedure within the temporal integration to dynamically adapt the computational grid and maintain the accuracy of the solution of the PDE as it evolves. We present examples to highlight the accuracy and adaptivity of our approach.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1993

Rational trigonometric approximations using Fourier series partial sums

A class of approximations (S(sub N,M)) to a periodic function f which uses the ideas of Pade, or rational function, approximations based on the Fourier series representation of f, rather than on the Taylor series representation of f, is introduced and studied. Each approximation S(sub N,M) is the quotient of a trigonometric polynomial of degree N and a trigonometric polynomial of degree M. The coefficients in these polynomials are determined by requiring that an appropriate number of the Fourier coefficients of S(sub N,M) agree with those of f. Explicit expressions are derived for these coefficients in terms of the Fourier coefficients of f. It is proven that these 'Fourier-Pade' approximations converge point-wise to (f(x(exp +))+f(x(exp -)))/2 more rapidly (in some cases by a factor of 1/k(exp 2M)) than the Fourier series partial sums on which they are based. The approximations are illustrated by several examples and an application to the solution of an initial, boundary value problem for the simple heat equation is presented.

Geer, James F.↗
DOE OSTI2025

Multi-invariants and bulk replica symmetry

In this paper, we analyze the question of replica symmetry in the bulk for multi-partite entanglement measures in the vacuum state of two dimensional holographic CFTs. We first define a class of multi-partite local unitary invariants, multi-invariants , with a given replica symmetry that acts freely and transitively on the replicas. We look for a subclass of measures such that the dual bulk geometry also preserves replica symmetry. We obtain the most general solution to this problem if we require the bulk to preserve replica symmetry for general configurations of the regions. Orbifolding the bulk solution with the replica symmetry gives us a bulk geometry with a network of conical singularities. Our approach makes it clear that there are infinitely many infinitely large families of multi-invariants such that each family evaluates identically on the holographic state. Geometrically, these are equalities involving volumes of handlebodies, possibly of different genus, at particular points in the moduli space. In certain cases, we check our bulk computation with an explicit calculation in CFT. Finally we comment on the generalization to higher dimension.

AdS-CFT Correspondence↗
DOE OSTI2025

Simulating Droplet-Resolved Haze and Cloud Chemistry Forming Secondary Organic Aerosols in Turbulent Conditions within Laboratory and Cloud Parcels

Most of our existing knowledge of cloud chemistry in regards to forming secondary organic aerosols (SOA) is based on measurements in bulk aqueous solutions. However, SOA reaction kinetics derived from bulk solution measurements might differ from the kinetics in actual cloud droplets, since turbulent mixing and ionic strengths, and ratio of surface area to volume in individual cloud droplets might vary substantially from bulk solutions in the real atmosphere. Three-dimensional models at various scales have been used to simulate aqueous chemistry. However, most of these models do not resolve turbulence down to the smallest length scales of 1 mm and do not simulate cloud chemistry in individual cloud droplets due to large computational costs. Here we incorporate the formation of isoprene epoxydiol SOA (IEPOX-SOA) in individual droplets within a one-dimensional explicit mixing parcel model (EMPM-Chem). We apply EMPM-Chem to simulate turbulence and droplet-resolved IEPOX-SOA formation using a configuration based on the Michigan Tech Pi chamber. We find that the dissolution of IEPOX gases is weighted more towards larger cloud droplets due to their large liquid water content (compared to smaller droplets), while the conversion of dissolved IEPOX to IEPOX-SOA is much greater within smaller deliquesced haze particles due to their higher acidity and ionic strengths compared to cloud droplets. We also find that as droplet residence times increase in the chamber, e.g., due to increasing ammonium bisulfate seed aerosol injection rates and/or increasing heights of the chamber, formation of IEPOX-SOA increases substantially. Thus, our EMPM-Chem model could be used to design future cloud chambers to maximize SOA production from cloud chemistry. We also apply the EMPM-Chem model to simulate how IEPOX-SOA formation evolves in individual cloud droplets within rising cloudy parcels in the atmosphere. We find that as subsaturated air is entrained into and turbulently mixed with the cloud parcel, evaporation causes a reduction in droplet sizes, which leads to corresponding increases in per droplet ionic strength and acidity. Increased droplet acidity in turn greatly accelerates the kinetics of IEPOX-SOA formation. In conclusion, our results provide key insights into single-cloud-droplet chemistry, suggesting that entrainment mixing may be an important process that increases SOA formation in the real atmosphere.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Electrochemical CO Reduction: A Property of the Electrochemical Interface

Electrochemical CO reduction holds the promise to be a cornerstone for sustainable production of fuels and chemicals. However, the underlying understanding of the carbon–carbon coupling toward multiple-carbon products is not complete. Here we present thermodynamically realistic structures of the electrochemical interfaces, determined by explicit ab initio simulations. We investigate how key CO reduction reaction intermediates are stabilized in different electrolytes and at different pH values. We find that the catalytic trends previously observed experimentally can be explained by the interplay between the metal surface and the electrolyte. For the Cu(100) facet with a phosphate buffer electrolyte, the energy efficiency is found to be limited by blocking of a phosphate anion, while in alkali hydroxide solutions (MOH, M = Na, K, Cs), OH* intermediates may be present, and at high overpotential the H* coverage limits the reaction. Furthermore the results provide insight into the electrochemical interface structure, revealing the limitations for multiple-carbon products, and offer a direct comparison to experiments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Search for exact local Hamiltonians for general fractional quantum Hall states

We report on our systematic attempts at finding local interactions for which the lowest-Landau- level projected composite-fermion wave functions are the unique zero energy ground states. For this purpose, we study in detail the simplest non-trivial system beyond the Laughlin states, namely bosons at filling factor ν = 2/3 and identify local constraints among clusters of particles in the ground state. By explicit calculation, we show that no Hamiltonian up to (and including) four particle in- teractions produces this state as the exact ground state, and speculate that this remains true even when interaction terms involving greater number of particles are included. Surprisingly, we can iden- tify an interaction, which imposes an energetic penalty for a specific entangled configuration of four particles with relative angular momentum of 6h, that produces a unique zero energy solution (as we have confirmed for up to 12 particles). This state, referred to as the λ-state, is not identical to the projected composite-fermion state, but the following facts suggest that the two might be topologi- cally equivalent: the two sates have a high overlap; they have the same root partition; the quantum numbers for their neutral excitations are identical; and the quantum numbers for the quasiparticle excitations also match. On the quasihole side, we find that even though the quantum numbers of the lowest energy states agree with the prediction from the composite-fermion theory, these states are not separated from the others by a clearly identifiable gap. This prevents us from making a conclusive claim regarding the topological equivalence of the λ state and the composite-fermion state. Lastly, our study illustrates how new candidate states can be identified from constraining selected many particle configurations and it would be interesting to pursue their topological classification.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
NASA NTRS1990

Three-dimensional flux-split Euler schemes involving unstructured dynamic meshes

Improved algorithms for the solution of the three-dimensional time-dependent Euler equations are presented for aerodynamic analysis involving unstructured dynamic meshes. The improvements have been developed recently to the spatial and temporal discretizations used by unstructured grid flow solvers. The spatial discretization involves a flux-split approach which is naturally dissipative and captures shock waves sharply with at most one grid point within the shock structure. The temporal discretization involves either an explicit time-integration scheme using a multi-stage Runge-Kutta procedure or an implicit time-integration scheme using a Gauss-Seidel relaxation procedure which is computationally efficient for either steady or unsteady flow problems. With the implicit Gauss-Seidel procedure, very large time steps may be used for rapid convergence to steady state, and the step size for unsteady cases may be selected for temporal accuracy rather than for numerical stability. Steady flow results are presented for both the NACA 0012 airfoil and the ONERA M6 wing to demonstrate applications of the new Euler solvers. The paper presents a description of the Euler solvers along with results and comparisons which assess the capability.

Batina, John T.↗
DOE OSTI2022

Accelerating Collective Communication in Data Parallel Training across Deep Learning Frameworks

This work develops new techniques within Horovod, a generic communication library supporting data parallel training across deep learning frameworks. In particular, we improve the Horovod control plane by implementing a new coordination scheme that takes advantage of the characteristics of the typical data parallel training paradigm, namely the repeated execution of collectives on the gradients of a fixed set of tensors. Using a caching strategy, we execute Horovod’s existing coordinator-worker logic only once during a typical training run, replacing it with a more efficient decentralized orchestration strategy using the cached data and a global intersection of a bitvector for the remaining training duration. Next, we introduce a feature for end users to explicitly group collective operations, enabling finer grained control over the communication buffer sizes. To evaluate our proposed strategies, we conduct experiments on a world-class supercomputer — Summit. We compare our proposals to Horovod’s original design and observe 2x performance improvement at a scale of 6000 GPUs; we also compare them against tf.distribute and torch.DDP and achieve 12% better and comparable performance, respectively, using up to 1536 GPUs; we compare our solution against BytePS in typical HPC settings and achieve about 20% better performance on a scale of 768 GPUs. Finally, we test our strategies on a scientific application (STEMDL) using up to 27,600 GPUs (the entire Summit) and show that we achieve a near-linear scaling of 0.93 with a sustained performance of 1.54 exaflops (with standard error +- 0.02) in FP16 precision.

Romero, Joshua↗
DOE OSTI2022

Stability Analysis of Coupled Advection-Diffusion Models with Bulk Interface Condition

Numerical stability is of critical importance in general circulation models because it affects the design of algorithms, time to solution, and computational costs associated with the simulations, which are very expensive in practice. In this paper we extend the stability analysis for ocean-atmosphere coupling proposed in [Zhang et al., J. Sci. Comput. 84, 44(2020)] to a more realistic model that includes horizontal advection. We analyze various time-stepping strategies. We find that advection has a stabilizing effect in scenarios common to climate models when bulk interface condition and explicit flux coupling are used. We also show that our method can be used to study the stability impact of advection for other interface conditions such as Dirichlet-Neumann conditions.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

A computationally efficient algorithm for computing convex hull prices

Electricity markets worldwide allow participants to bid non-convex production offers. While non-convex offers can more accurately reflect a resource's capabilities, they create challenges for market clearing processes. For example, system operators may be required to execute side payments to participants whose costs are not covered through energy sales as determined via traditional locational marginal pricing schemes. Convex hull pricing minimizes this and other types of side payments while providing uniform (i.e., locationally and temporally consistent) prices. Computing convex hull prices involves solving either a large-scale linear program or the Lagrangian dual of the corresponding non-convex scheduling problem. Further, the former approach requires explicit descriptions of market participants' convex hulls. While linear programs for computing convex hull prices are large, their structure is naturally decomposable by generators. Here, in this work, we propose and empirically analyze a Benders decomposition approach to computing convex hull prices that leverages recent advances in convex hull formulations for thermal generating units. We demonstrate across a large set of test instances that our decomposition approach only requires modest computational effort, obtaining solutions at least an order of magnitude faster than the equivalent large-scale linear programming approach. Overall, we provide a computationally feasible method for computing convex hull prices for industrial scale market clearing problems, enabling the possibility of practical adoption of this advanced pricing mechanism.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

A phenology- and trend-based approach for accurate mapping of sea-level driven coastal forest retreat

The rapid replacement of upland forest by encroaching marshland is a striking manifestation of global sea-level rise (SLR). Timely and high-resolution information on the location and extent of transition forest (the ecotone between upland forest and marsh where tree mortality due to seawater intrusion begins) is fundamental to understanding the processes and patterns of SLR-driven landscape reorganization. Despite its significance, accurate characterization of salt-impacted transition forest remains challenging due to the complexity of coastal environments, scarcity of ground-truth data, and the lack of effective mapping algorithms. Here we use the full archive of Landsat images between 1984 and 2021 to investigate the spectral, temporal, and phenological characteristics of transition forest, and develop a robust framework for monitoring coastal vegetation shifts in the mid-Atlantic U.S., a global SLR hotspot. Here, we found that transition forest exhibits strong negative NDVI trends and a deviation of land surface phenology from marsh and upland forest that distinguishes itself from surrounding vegetation. By integrating temporal trends and land surface phenology, our results demonstrate superior discrimination between marsh and coastal forests to existing map products (e.g. NOAA Coastal Change Analysis Program, National Land Cover Database) that allows a reliable identification of the coastal treeline. We applied the approach to map regional land cover in 1985, 2000 and 2020 (overall classification accuracy >92%) and found that the area of coastal forest decreased by 22.0% from 1985 to 2020, the majority of which transitioned to marshland (92.3%, 5.3 × 10 3 ha). Based upon fine-scale patterns of coastal transgression, we created a practical workflow for spatially explicit quantification of forest retreat rates. Concurrent with rising sea level, coastal forests migrated upslope from 0.63 (± 0.27) m above sea level in 1985 to 0.78 (± 0.32) m above sea level in 2020, and horizontal forest retreat rates accelerated from 3.1 (range of 0–36) m yr -1 during 1985–2000 to 4.7 (0–55) m yr -1 during 2001–2020. As SLR continues to accelerate, our study may serve as a scalable solution for consistent tracking of coastal landscape evolution that is urgently needed for sustainable forest and wetland management.

54 ENVIRONMENTAL SCIENCES↗