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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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At least 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Astrometric microlensing probes of the isolated neutron star population with Roman

Notoriously hard to detect and study, isolated neutron stars (NSs) might provide valuable answers to fundamental questions about stellar evolution and explosion physics. With the upcoming Roman Space Telescope, scheduled for launch in 2026, a new and powerful channel for their detection will become available: astrometric microlensing. We set out to create a realistic sample of simulated gravitational microlensing events as observed by Roman with the Galactic Bulge Time Domain Survey. We focus in particular on the population of NS lenses, which has until now been largely understudied. We used dedicated Galactic models tailored for application to microlensing by compact objects. In addition to populations of stars, white dwarfs, and black holes, we simulated four different NS populations with Maxwellian natal kick distributions: v = (150, 250, 350, 450) km/s. For each simulation, we applied projected Roman precision, cadence, and detectability criteria. We found that the parameter space log10 t E –log 10 θ E , which will be accessible to Roman observations, is efficient for the classification of stellar remnants. We found a feature in this space that is characteristic of NSs; using this feature, optimal samples of NS candidates can be constructed from Roman -like datasets. We describe the dependence of the observable parameter distributions on the assumed mean kick velocities. As the effects of natal kicks are very complex and mutually counteracting, we suggest that more detailed studies focused on the dynamics of NSs are needed in anticipation of Roman and future surveys. We estimate that Roman will observe approximately 11 000 microlensing events, including ~100 with NS lenses, whose photometric and astrometric signals are detectable; the event yield decreases by 38% when gap-filling low-cadence observations are not included. We make all simulated microlensing event datasets publicly available in preparation for Roman data.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Spatio-Temporal Surrogates for Interaction of a Jet with High Explosives: Part II - Clustering Extremely High-Dimensional Grid-Based Data

Building an accurate surrogate model for the spatio-temporal outputs of a computer simulation is a challenging task. A simple approach to improve the accuracy of the surrogate is to cluster the outputs based on similarity and build a separate surrogate model for each cluster. This clustering is relatively straightforward when the output at each time step is of moderate size. However, when the spatial domain is represented by a large number of grid points, numbering in the millions, the clustering of the data becomes more challenging. In this report, we consider output data from simulations of a jet interacting with high explosives. These data are available on spatial domains of different sizes, at grid points that vary in their spatial coordinates, and in a format that distributes the output across multiple files at each time step of the simulation. We first describe how we bring these data into a consistent format prior to clustering. Borrowing the idea of random projections from data mining, we reduce the dimension of our data by a factor of thousand, making it possible to use the iterative k-means method for clustering. We show how we can use the randomness of both the random projections, and the choice of initial centroids in k-means clustering, to determine the number of clusters in our data set. Our approach makes clustering of extremely high dimensional data tractable, generating meaningful cluster assignments for our problem, despite the approximation introduced in the random projections.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Applicability of 1D site response analysis to shallow sedimentary basins: A critical evaluation through physics-based 3D ground motion simulations

One-dimensional site response analysis (1D SRA) remains the standard practice in considering the effect of local soil deposits and predicting site-specific ground motions, although its range of applicability to realistic seismic wavefields is still in question. In this 1D approach, horizontal and vertical ground shaking are assumed to be induced by vertically propagating shear and compressional waves, respectively. A recent study based on analytical two-dimensional (2D) plane waves and simple point source earthquake simulations has shown two mechanistic limitations in this 1D modelling technique for general inclined seismic waves, that is, systematic over-prediction of the vertical motion and wave trapping in the 1D soil column. In this article, we evaluate in detail the applicability of this 1D modelling approach to realistic three-dimensional (3D) simulated seismic wavefields in shallow sedimentary basins. Linear-viscoelastic 1D SRA predictions using two types of input motions that are commonly used in practice—rock outcrop and in-column motions, are compared with the reference true site response results from 3D earthquake simulations in terms of various measures in the frequency and time domain. It is shown that the horizontal motion in the 3D seismic wavefield exhibits dominant shear wave propagation phenomenon, while the vertical motion is a combined effect of compressional and shear waves and can be over-predicted by the 1D approach when the incident seismic waves are inclined. Direct evidence of the wave refraction process that leads to the vertical motion over-prediction is provided. 1D SRA with in-column inputs can yield motions that have significantly longer duration compared to the true 3D site response solution due to trapped waves, casting in doubt the frequent need for increased soil damping in existing site studies to compensate for wave attenuation due to scattering alone. Sensitivity investigation on the increase of soil profile damping by a multiplier D mul shows D mul values compatible with those found in the literature for both horizontal and vertical motions. It is shown that the level of D mul optimized for a best match of the spectral acceleration is dependent on the characteristic of the input motion and a larger D mul is typically required for the vertical component. In contrast, 1D SRA with outcrop motions predicts motions with shorter significant duration due to its inability to capture the basin-edge generated surface waves. A suite of ground motion simulations was performed to assess the sensitivity of the observations to the basin geologic structure including the velocity gradient, rock-basin impedance contrast and basin depth. The analysis results show that the accuracy of the simplified 1D procedure is dependent on the wavefield composition of both the input motions and the true 3D site response solution. While the horizontal motions in shallow sedimentary basins can, to the first order, be reasonably captured by the simplified 1D approach, 1D SRA for the vertical component is in general not reliable and contributions from inclined shear waves should be accounted for in site-specific evaluation of the vertical design ground motion.

1D assumption↗
DOE OSTI2020

On the advantages of exploiting memory in Markov state models for biomolecular dynamics

Biomolecular dynamics play an important role in numerous biological processes. Markov State Models (MSMs) provide a powerful approach to study these dynamic processes by predicting long time scale dynamics based on many short molecular dynamics (MD) simulations. In an MSM, protein dynamics are modeled as a kinetic process consisting of a series of Markovian transitions between different conformational states at discrete time intervals (called “lag time”). To achieve this, a master equation must be constructed with a sufficiently long lag time to allow interstate transitions to become truly Markovian. This imposes a major challenge for MSM studies of proteins since the lag time is bound by the length of relatively short MD simulations available to estimate the frequency of transitions. Here, we show how one can employ the generalized master equation formalism to obtain an exact description of protein conformational dynamics both at short and long time scales without the time resolution restrictions imposed by the MSM lag time. Using a simple kinetic model, alanine dipeptide, and WW domain, we demonstrate that it is possible to construct these quasi-Markov State Models (qMSMs) using MD simulations that are 5–10 times shorter than those required by MSMs. These qMSMs only contain a handful of metastable states and, thus, can greatly facilitate the interpretation of mechanisms associated with protein dynamics. A qMSM opens the door to the study of conformational changes of complex biomolecules where a Markovian model with a few states is often difficult to construct due to the limited length of available MD simulations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Real-Time Lifetime Prediction of Semiconductor Devices Using Hardware-in-the-Loop

This paper presents a unique approach to enable real-time lifespan prediction of semiconductor power modules using a Hardware-in-the-Loop (HIL) system. By integrating the module's overall loss characteristics-specifically switching and conduction losses-with a thermoelectric model of the thermal management system, this research demonstrates that the model can dynamically estimates the junction temperature profile of the semiconductor devices in response to a changing torque demand profile for the motor drive system. This capability enables continuous monitoring of the module's operational time and cumulative stress induced on the devices to compute accumulated remaining lifetime or time-to-failure (TTF). This study provides an architectural framework for the HIL system with high-fidelity component models of multiple physical domains, allowing simulation of dynamic behaviors of a closely-coupled motor drive system. The advanced real-time computation and measurement functionalities of the HIL system allow for both dynamic lifetime calculations based on simulated data and aggregate lifetime predictions utilizing historical data. Moreover, this paper details an algorithm that not only computes cumulative damage but also synthesizes these data into a comprehensive aggregated lifetime metric. This methodology can enhance the maintenance scheduling strategies and operational reliability of semiconductor devices in critical applications, ultimately extending their service life while optimizing performance.

hardware-in-the-loop (HIL)↗
DOE OSTI2023

Convergence of small scale Ly α structure at high- z under different reionization scenarios

ABSTRACT The Ly α forest (LAF) at z > 5 probes the thermal and reionization history of the intergalactic medium (IGM) and the nature of dark matter, but its interpretation requires comparison to cosmological hydrodynamical simulations. At high-z, convergence of these simulations is more exacting since transmission is dominated by underdense voids that are challenging to resolve. With evidence mounting for a late end to reionization, small structures down to the sub-kpc level may survive to later times than conventionally thought due to the reduced time for pressure smoothing to impact the gas, further tightening simulation resolution requirements. We perform a suite of simulations using the Eulerian cosmological hydrodynamics code Nyx, spanning domain sizes of 1.25 − 10 h−1 Mpc and 5 − 80 h−1 kpc cells, and explore the interaction of these variables with the timing of reionization on the properties of the matter distribution and the simulated LAF at z = 5.5. In observable Ly α power, convergence within 10 per cent is achieved for k < 0.1 s km–1, but larger k shows deviation of up to 20 per cent. While a later reionization retains more small structure in the density field, because of the greater thermal broadening there is little difference in the convergence of LAF power between early (z = 9) and later (z = 6) reionizations. We conclude that at z ∼ 5.5, resolutions of 10 kpc are necessary for convergence of LAF power at k < 0.1 s km–1, while higher-k modes require higher resolution, and that the timing of reionization does not significantly impact convergence given realistic photoheating.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

The Simons Observatory: validation of reconstructed power spectra from simulated filtered maps for the small aperture telescope survey

We present a transfer function-based method to estimate angular power spectra from filtered maps for cosmic microwave background (CMB) surveys. This is especially relevant for experiments targeting the faint primordial gravitational wave signatures in CMB polarisation at large scales, such as the Simons Observatory (SO) small aperture telescopes. While timestreams can be filtered to mitigate the contamination from low-frequency noise, usual methods that calculate the mode coupling at individual multipoles can be challenging for experiments covering large sky areas or reaching few-arcminute resolution. The method we present here, although approximate, is more practical and faster for larger data volumes. We validate it through the use of simulated observations approximating the first year of SO data, going from half-wave plate-modulated timestreams to maps, and using simulations to estimate the mixing of polarisation modes induced by an example of time-domain filtering. We show its performance through an example null test and with an end-to-end pipeline that performs inference on cosmological parameters, including the tensor-to-scalar ratio r. The performance demonstration uses simulated observations at multiple frequency bands. We find that the method can recover unbiased parameters for our simulated noise levels.

CMBR experiments↗
DOE OSTI2020

Domain-specific compilers for dynamic simulations of quantum materials on quantum computers

Abstract Simulation of the dynamics of quantum materials is emerging as a promising scientific application for noisy intermediate-scale quantum (NISQ) computers. Due to their high gate-error rates and short decoherence times, however, NISQ computers can only produce high-fidelity results for those quantum circuits smaller than some given circuit size. Dynamic simulations, therefore, pose a challenge as current algorithms produce circuits that grow in size with each subsequent time-step of the simulation. This underscores the crucial role of quantum circuit compilers to produce executable quantum circuits of minimal size, thereby maximizing the range of physical phenomena that can be studied within the NISQ fidelity budget. Here, we present two domain-specific (DS) quantum circuit compilers for the Rigetti and IBM quantum computers, specifically designed to compile circuits simulating dynamics under a special class of time-dependent Hamiltonians. The compilers outperform state-of-the-art general-purpose compilers in terms of circuit size reduction by around 25%–30% as well as wall-clock compilation time by around 40% (dependent on system size and simulation time-step). Drawing on heuristic techniques commonly used in artificial intelligence, both compilers scale well with simulation time-step and system size. Code for both compilers is open-source and packaged into a full-stack quantum simulation software with tutorials included for ease of use for future researchers wishing to perform dynamic simulations of quantum materials on quantum computers. As our DS compilers provide significant improvements in both compilation time and simulation fidelity, they provide a building block for accelerating progress toward physical quantum supremacy.

Physics↗
DOE OSTI2020

Discrete Fracture Network Modeling to Estimate Upscaled Parameters for the Topopah Spring, Lava Flow, and Tiva Canyon Aquifers at Pahute Mesa, Nevada National Security Site

This report describes the results of Discrete Fracture Network (DFN) simulations for the Topopah Spring Aquifer (TSA), Lava Flow Aquifer, and Tiva Canyon Aquifer (TCA), at Pahute Mesa on the Nevada National Security Site (NNSS), formerly the Nevada Test Site. The research focuses on calculating upscaled groundwater flow and contaminant transport parameters using DFNs generated according to fracture characteristics observed in the TSA, LFA and TCA at Pahute Mesa. The highly fractured and heterogeneous nature of these aquifers makes them candidates for stochastic DFN modeling of radionuclide transport on a small scale with subsequent upscaling. One hundred independent DFN realizations are generated for each aquifer, and the upscaled parameters for continuum simulations of subsurface flow and transport in fractured media at Pahute Mesa are calculated. Our goal is to implement a modeling approach that can translate parameters to larger-scale models that account for local-scale flow and transport processes, such as channelization of flow and transport along a few well connected, large fractures. Additionally, to simulate advective and advective-diffusive transport through the fracture networks, the Time Domain Random Walk (TDRW) approach is applied to account for matrix diffusion into a finite half-space. Moreover, a novel approach to calculate dynamic (active) fracture surface area to reflect flow channeling is implemented. This work will improve the representation of radionuclide transport processes in largescale, regulatory-focused models by providing estimates of hard-to-measure flow and contaminant transport parameters at large scales. In this report, we (1) show recent results of flow and transport simulations on multiple DFN realizations of the TSA, LFA, TCA; (2) discuss the resulting distributions of estimated upscaled parameters; (3) describe the estimation of upscaled parameters for an equivalent parallel-plate continuum model and (4) present a comparison between simulated transport from the equivalent continuum model and an actual DFN.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Computationally efficient subglacial drainage modelling using Gaussian process emulators: GlaDS-GP v1.0

Subglacial drainage models represent water flow at the ice–bed interface through coupled distributed and channelized systems to determine water pressure, discharge, and drainage system geometry. While they are used to understand processes such as the relationship between surface melt and ice flow, the number of uncertain model parameters and the computational cost of running models makes it difficult to adequately explore the high-dimensional parameter space and evaluate uncertainty in model predictions. Here, we develop Gaussian process (GP) emulators that make fast predictions with associated uncertainty of subglacial drainage model outputs. Using a truncated principal component (PC) basis representation, we construct a GP emulator for diurnally averaged subglacial water pressure. We also explore emulation of scalar variables describing drainage efficiency and configuration. We train the emulators using ensembles of up to 512 simulations varying eight parameters of the Glacier Drainage System (GlaDS) model on a synthetic domain intended to represent an ice-sheet margin. The emulators make predictions ∼ 1000 times faster than GlaDS simulations, with errors <3 % for the water pressure field and ∼ 5 %–9 % for drainage efficiency and configuration. We apply the emulators to explore the eight-dimensional parameter space by computing variance-based parameter sensitivity indices, finding that three parameters (ice flow coefficient, bed bump aspect ratio, and the subglacial cavity system conductivity) explain 90 % of the variance in modelled water pressure in response to parameter changes. The GP emulator approach described here is well suited to integrating observational data with models to make calibrated, credible predictions of subglacial drainage.

58 GEOSCIENCES↗
DOE OSTI2020

Preliminary results in using Deep Learning to emulate BLOB, a nuclear interaction model

Purpose: A reliable model to simulate nuclear interactions is fundamental for Ion-therapy. We already showed how BLOB (“Boltzmann-Langevin One Body”), a model developed to simulate heavy ion interactions up to few hundreds of MeV/u, could simulate also 12 C reactions in the same energy domain. However, its computation time is too long for any medical application. For this reason we present the possibility of emulating it with a Deep Learning algorithm. Methods: The BLOB final state is a Probability Density Function (PDF) of finding a nucleon in a position of the phase space. We discretised this PDF and trained a Variational Auto-Encoder (VAE) to reproduce such a discrete PDF. As a proof of concept, we developed and trained a VAE to emulate BLOB in simulating the interactions of 12 C with 12 C at 62 MeV/u. To have more control on the generation, we forced the VAE latent space to be organised with respect to the impact parameter (b) training a classifier of b jointly with the VAE. Results: In this work, the distributions obtained from the VAE are similar to the input ones and the computation time needed to use the VAE as a generator is negligible. Conclusions: We show that it is possible to use a Deep Learning approach to emulate a model developed to simulate nuclear reactions in the energy range of interest for Ion-therapy. We foresee the implementation of the generation part in C++ and to interface it with the most used Monte Carlo toolkit: Geant4.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Thermal coupling-decoupling mechanism of heat transfer across van der Waals interfaces in n-eicosane

Progress toward improving thermal transport properties of n-eicosane, a promising phase change material for thermal energy storage near human body temperature, is hindered by lack of a general theoretical framework to model thermal interfacial conductance (TIC) of the van der Waals (vdW) force bonded molecular interfaces, which have little compositional/structural mismatch. Combining molecular dynamics simulations at temperatures up to the melting point and a time-domain analysis of interfacial heat currents in individual molecules, we unveil that (1) the heat flux across a molecular vdW interface has an alternating coupling-decoupling pattern at the single molecule level due to thermal fluctuations, and (2) the net heat transfer during the thermally coupled periods is orders of magnitude larger than that during the thermally decoupled periods. Furthermore, we demonstrate that a vdW interface's TIC correlates almost linearly with two atomistic-scale coupling-decoupling parameters: αc and σc, that represent the duration and strength of the thermal coupling, respectively. This thermal coupling-decoupling mechanism proposes a new paradigm that explicitly accounts for the effects of structural flexibility and dynamical fluctuation on heat transfer across molecular interfaces, and will likely provide new insights into modeling thermal transport properties in a wide-ranging soft materials, including self-assembled monolayers, paraffins or lipids.

42 ENGINEERING↗
DOE OSTI2020

Robust late twenty-first century shift in the regional monsoons in RegCM-CORDEX simulations

Abstract We use an unprecedented ensemble of regional climate model (RCM) projections over seven regional CORDEX domains to provide, for the first time, an RCM-based global view of monsoon changes at various levels of increased greenhouse gas (GHG) forcing. All regional simulations are conducted using RegCM4 at a 25 km horizontal grid spacing using lateral and lower boundary forcing from three General Circulation Models (GCMs), which are part of the fifth phase of the Coupled Model Inter-comparison Project (CMIP5). Each simulation covers the period from 1970 through 2100 under two Representative Concentration Pathways (RCP2.6 and RCP8.5). Regional climate simulations exhibit high fidelity in capturing key characteristics of precipitation and atmospheric dynamics across monsoon regions in the historical period. In the future period, regional monsoons exhibit a spatially robust delay in the monsoon onset, an increase in seasonality, and a reduction in the rainy season length at higher levels of radiative forcing. All regions with substantial delays in the monsoon onset exhibit a decrease in pre-monsoon precipitation, indicating a strong connection between pre-monsoon drying and a shift in the monsoon onset. The weakening of latent heat driven atmospheric warming during the pre-monsoon period delays the overturning of atmospheric subsidence in the monsoon regions, which defers their transitioning into deep convective states. Monsoon changes under the RCP2.6 scenario are mostly within the baseline variability.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

High-Resolution Simulations of Geological CO 2 Injection: Application to the SPE11 Benchmark

Geological carbon sequestration (GCS) will play a critical role in decarbonization and in facilitating the transition to clean energy systems. Because CO 2 is highly mobile, ensuring its safe and permanent injection into subsurface geological formations involves monitoring over larger spatial domains and longer time periods than is typical for hydrocarbon reservoirs. This can benefit from simulation tools capable of modeling key CO 2 trapping mechanisms, particularly those optimized for speed and scalability on high-performance computing systems. Using isothermal versions of the SPE11B and SPE11C benchmark cases, we conduct a mesh refinement study simulating CO 2 injection into kilometer-scale rock formations at centimeter resolution with the GEOS open-source simulation framework. We focus on how mesh refinement improves the accuracy of convective mixing in both 2D and 3D simulations. The computational costs associated with achieving a converged solution highlight the need for predictive upscaling techniques. A systematic performance scaling analysis—including both central processing unit (CPU) and graphics processing unit (GPU) architectures—complements the “Results” section.

Geosciences↗
DOE OSTI2024

Train small, model big: Scalable physics simulators via reduced order modeling and domain decomposition

Numerous cutting-edge scientific technologies originate at the laboratory scale, but transitioning them to practical industry applications is a formidable challenge. Traditional pilot projects at intermediate scales are costly and time-consuming. An alternative, the pilot-scale model, relies on high-fidelity numerical simulations, but even these simulations can be computationally prohibitive at larger scales. To overcome these limitations, we propose a scalable, physics-constrained reduced order model (ROM) method. The ROM identifies critical physics modes from small-scale unit components, projecting governing equations onto these modes to create a reduced model that retains essential physics details. We also employ Discontinuous Galerkin Domain Decomposition (DG-DD) to apply ROM to unit components and interfaces, enabling the construction of large-scale global systems without data at such large scales. Here this method is demonstrated on the Poisson and Stokes flow equations, showing that it can solve equations about 15–40 times faster with only ~1% relative error. Furthermore, ROM takes one order of magnitude less memory than the full order model, enabling larger scale predictions at a given memory limitation.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Modeled estimates of permafrost hydrology and related fields for pan-Arctic region over the period 1980-2100

This dataset contains gridded estimates of total runoff (mm/day); subsurface runoff (mm/day); snow water equivalent (SWE, mm/day); vertical upward water flux of combined surface evaporation, evapotranspiration, and snow sublimation (mm/day); and soil temperature (C) across the pan-Arctic basin from simulations of the Permafrost Water Balance Model (PWBM v4). These data were generated to allow researchers to advance understanding of the changes unfolding in the Arctic's terrestrial water cycle under the influences of climate warming, hydrological cycle intensification, and permafrost thaw. The dataset will enable researchers to address important questions spanning multiple disciplines. For example, how will rising river flows exported to the coast impact critical zone ecosystems, near-shore ice dynamics, and ocean biogeochemical processes. Spatial resolution is 25x25 km with N=39926 grid cells spanning the domain. Three forcing datasets were used to drive simulations at an implicit daily time step over the period 1980-2100. Daily air temperature, precipitation, and wind speed data from the WATCH Forcing Data methodology applied to ERA5 reanalysis (W5E5) were used for meteorological forcings over the period 1980-2019. Simulations for the period 1980-2100 used meteorological data from two global climate models; IPSL-CM6A-LR and MPI-ESM1-2-HR. The PWBM hydrological outputs are organized by grid and month in gzipped ASCII text files within each archived tar file. Soil temperature is organized by grid cell and day of year from DOY 205 to DOY 260. No special software is required to work with these data. The package contains spatial domain and river basin information files. These data are most useful for analyses of the spatial and temporal variations in terrestrial hydrology and soil thermal dynamics. A manuscript describing the model simulations and associated analysis has been accepted for publication in The Cryosphere (Rawlins and Karmalkar, 2024).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Influence of defects on the femtosecond laser damage resistance of multilayer dielectric gratings

Multilayer dielectric (MLD) gratings with high diffraction efficiency and a high laser-induced damage (LID) threshold for pulse compressors are key to scaling the peak and average power of chirped pulse amplification lasers. However, surface defects introduced by manufacturing, storage, and handling processes can reduce the LID resistance of MLD gratings and impact the laser output. The underlying mechanisms of such defect-initiated LID remain unclear, especially in the femtosecond regime. In this Letter, we model dynamic processes in interactions of a 20-fs near-infrared (NIR) laser pulse and a MLD grating design in the presence of cylindrically symmetrical nodules and particle contaminants and cracks at the surface. Utilizing a dynamic model based on a 2D finite difference in time domain (FDTD) field solver coupled with photoionization, electron collision, and refractive index modification, we study the simulation results for the damage site distribution initiated by defects of various types and sizes and its impact on the LID threshold of the grating design.

Zhang, Simin (ORCID:0000000174948230)↗
DOE OSTI2026

Entropy Stable Conservative Flux Form Neural Networks

We propose an entropy-stable conservative flux form neural network (CFN) to predict the dynamics of unknown governing conservation laws. The design of the network is based on the entropy-stable, second-order, and non-oscillatory Kurganov-Tadmor (KT) scheme. The proposed entropy-stable CFN, hereafter referred to as ESCFN, uses slope limiting as a denoising mechanism, ensuring accurate predictions in both noisy and sparse observation environments, as well as in both smooth and discontinuous regions. Importantly, our method is designed to predict long term dynamics of the unknown conservation law exclusively from a short temporal window of observed data, that is, without oracle knowledge of the PDE or later-time solution profiles. Numerical experiments demonstrate that the ESCFN achieves both stability and conservation while maintaining accuracy over extended time domains, and successfully predicts shock propagation speeds in long-term simulations. Furthermore, it is also robust to both noisy and sparse data environments.

Hyperbolic conservation laws↗