Search NASA⌕ Search

SEARCH · Search NASA

Results for “Working Fluid demonstrates”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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

At least 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Utah FORGE: Fault Shear Reactivation Experimental Data for Fluid Injection-Rate Controls on Seismic Moment

Included are experimental data recorded from shear experiments that specifically explore the link between fluid-injection rate and seismic moment resulting from shear reactivation of laboratory faults. Raw mechanical data from three experiments are included alongside corresponding MATLAB scripts that import and plot the data, as well as use it to calculate shear and normal stress. Experiments are performed on 2.5-3 inch long granitoid cores from the Utah FORGE EGS demonstration site, containing a single inclined fracture with small-scale roughness added to the fracture surface. The raw data included here were recorded from an aluminum triaxial pressure vessel (TEMCO) configured with three independent servo-controlled pumps, with distilled water used as the working fluid. The pumps control confining pressure, upstream pore pressure, and axial pressure, with each pump connected to a LabView interface to record applied pressures, cumulative injected water volumes, and pump flow rates. The downstream outlet from the fracture is closed to allow pressurization, which is measured by an external pressure transducer. A linear variable differential transformer (LVDT) attached to the axial piston measures axial displacement, from which we calculate shear displacement along the fracture. Additionally, P-wave transducers are used to record acoustic signatures, where acoustic emission events and maximum amplitudes are compared against seismic moment and shear slip velocity. Fluid injection rates range between 0.05 mL/min, 0.25 mL/min, and 0.75 mL/min for each experiment. Along-fault pressure distributions are progressively less uniform as injection rates increase, representing a switch from steady-state to transient conditions. Triggered shear displacement is used as a proxy for seismic moment and is indexed against cumulative injection volume and rate. Each experiment is performed under constant shear stress conditions, and the sample is fully saturated with DI water. Axial and confining stresses are applied to 3 MPa through pressure-stepping in 500 kPa increments. The pore pressure is held constant at 200 kPa prior to initiating the experiment, and initial axial displacement is recorded. The axial stress is then increased to initiate shear mobilization during the loading phase (run-in) until a peak steady state is achieved. The initial shear stress is reduced to approximately 80% of the peak shear stress by decreasing the axial stress, then held constant for the duration of each experiment.

15 GEOTHERMAL ENERGY↗
DOE OSTI2023

Development and Porting of Nuclear Reactor Computational Models for the NRIC Virtual Test Bed in FY23

The U.S. DOE’s National Reactor Innovation Center (NRIC) hosts an open-source website and associated GitHub repository called the Virtual Test Bed (VTB) on which computational models for advanced reactors are documented and shared with the reactor community. In FY23 under the NRIC program, computational models for nuclear reactor analysis were developed and contributed to the VTB Github repository during FY23 by contributors at Argonne National Laboratory. Other models developed outside of NRIC were also ported to the VTB as part of this work, serving a broader mission to make computational reactor analysis models more widely available to the reactor community. The model development activities focused on demonstration of gas-cooled microreactor models including computational fluid dynamics simulations of flow through an industry-inspired air jacket design, and simulation of multiphysics transients for a gas-cooled microreactor assembly. Additionally, development of a molten salt reactor (led at Idaho National Laboratory) was supported through Argonne’s expertise in multigroup cross sections generation. Models for these two reactor types were targeted due to their relevancy to NRIC’s Demonstration of Microreactor Experiments (DOME) and Laboratory for Operation and Testing in the U.S. (LOTUS) physical test beds, which are slated to host microreactor and molten salt reactor experiments. The model porting activities consisted of developing detailed documentation for several physics models which originate from the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program. We include only contributions from Argonne National Laboratory in this report.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Continued Validation Studies using the MOOSE Framework for Plasma Simulation with Electromagnetics

Resources and tools for the modeling and simulation of low-temperature plasma (LTP) discharges are increasingly vital to progress in the field in order to properly characterize and study complex source designs and plasma chemistries beyond the scope of traditional diagnostics. Open-source software provides powerful platforms for this work and can enable community-driven LTP R&D. Within the Multiphysics Object-Oriented Simulation Environment (MOOSE) open-source framework [1], capabilities have been demonstrated in the areas of plasma fluids (Zapdos [2]), plasma chemistry (CRANE [3]), and general electromagnetic wave theory (Electromagnetic Library for Kinetics & fluids [ELK] [4]). ELK has since been coupled to Zapdos/CRANE to enable fully coupled electromagnetic plasma simulations. This talk will detail the continued validation efforts and discuss Zapdos-ELK-CRANE code coupling with various-low temperature plasma sources. The impact of fully coupled electromagnetics on process parameters (e.g., temperature and electron/ion energy) versus an electrostatic description will also be discussed. [1] Permann et al., SoftwareX, 11 (2020) 100430. [2] Lindsay et al., J. Phys. D: Appl. Phys. 49 (2016) 235204. [3] Keniley et al., Talk, GEC Session DT3.00002 (2019). [4] Icenhour et al., Talk, GEC Session RR1.00006 (2019). Acknowledgements: INL Graduate Fellowship Program, NSF SI2 Grant 1740300, U.S. Dept. of Energy Office of Science Graduate Student Research Program

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Performance characterization of freeform finished surfaces of potassium dihydrogen phosphate using fluid jet polishing with a nonaqueous slurry

Abstract Potassium dihydrogen phosphate (KDP) and its deuterated analog (DKDP) are unique nonlinear optical materials for high power laser systems. They are used widely for frequency conversion and polarization control by virtue of the ability to grow optical-quality crystals at apertures suitable for fusion-class laser systems. Existing methods for freeform figuring of KDP/DKDP optics do not produce surfaces with sufficient laser-induced–damage thresholds (LIDT’s) for operation in the ultraviolet portion of high-peak-power laser systems. In this work, we investigate fluid jet polishing (FJP) using a nonaqueous slurry as a sub-aperture finishing method for producing freeform KDP surfaces. This method was used to selectively polish surface areas to different depths on the same substrate with removals ranging from 0.16 μm to 5.13 μm. The finished surfaces demonstrated a slight increase in roughness as the removal depth increased along with a small number of fracture pits. Laser damage testing with 351 nm, 1 ns pulses demonstrated excellent surface damage thresholds, with the highest values in areas devoid of fracture pits. This work demonstrates, for the first time, a method that enables fabrication of a waveplate that provides tailored polarization randomization that can be scaled to meter-sized optics. Furthermore, this method is based on FJP technology that incorporates a nonaqueous slurry specially designed for use with KDP. This novel nonaqueous FJP process can be also used for figuring other types of materials that exhibit similar challenging inherent properties such as softness, brittleness, water-solubility, and temperature sensitivity.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Development and assessment of models for turbulent Rayleigh-Taylor mixing using the macroscopic forcing method

Reynolds-Averaged Navier Stokes (RANS) simulations are a popular method for designing ICF experiments, and accurate mixing models are crucial for these simulations to give good predictions. To this end, the present work seeks to demonstrate the Macroscopic Forcing Method (MFM) as a tool for both improving existing RANS models as well as assessing RANS model forms. First, MFM analysis from Lavacot et al. (Phys. Rev. Fluids, 2025) is used to develop the k–L–F model, an extension of the k–L model of Dimonte and Tipton (Phys. Fluids, 2006) that incorporates nonlocality through addition of a turbulent species flux transport equation. MFM is then applied to the k–L–F model along with the k–L and BHR–4 models to assess their forms and compare the model-implied eddy diffusivity moments to those measured from high-fidelity simulations. Furthermore, the analysis reveals that models incorporating nonlocality (k–L–F and BHR–4) match the high-fidelity simulation data better than purely local models (k–L), both in terms of mean fields and eddy diffusivity moments. However, all of the considered RANS models struggle to match temporal moments at high Atwood numbers, highlighting the importance of temporal nonlocality in these regimes and the need for additional improvement even among models incorporating nonlocality.

general physics↗
DOE OSTI2024

Runaway electron plateau current profile reconstruction from synchrotron imaging and Ar-II line polarization angle measurements in DIII-D

Abstract Current profile reconstructions are obtained for high current ( I p ≃ 550 kA) post-disruption runaway electron (RE) plateau plasmas in DIII-D. Two novel methods of measuring the RE current profile in high-current RE plateaus are introduced and compared: localization of the q = 2 rational surface using visible synchrotron emission (SE) imaging and the measurement of the polarization angle of line-integrated Ar-II line emission. The two methods are found to be consistent with each other within the data uncertainties. Different simulations of the RE current profile are compared with the measurements: the toroidal fluid RE model is found to best fit the data, within the measurement uncertainties. In addition to introducing two novel methods to measure the RE current profile and validating present simulation capabilities, this work demonstrates that instabilities can grow at q = 2 and q = 1 surfaces without necessarily causing a RE final loss instability. Numerical simulations are also presented to elucidate the role of these instabilities on synchrotron emission.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Scalable simulation of coupled adsorption and transport of methane in confined complex porous media with density preconditioning

The growing significance of shales and tight formations in the transition to less carbon-intensive and clean energy drives the research endeavor to understand the physics of gas flow within these systems. However, shales are composed of massively heterogeneous physical and chemical features. Most nano-sized pores connect to millimeter-scale fractures, leading to multiscale transport. These nano-scale pore throats demonstrate non-classical flow behavior, such as non-negligible slip velocities and adsorbed gas layers at the boundary. As a result, classical computational fluid dynamics models do not capture the physics. In this work, we develop a coupling scheme for the multiple-relaxation-time (MRT) lattice Boltzmann (LB) method that integrates the Peng-Robinson equation of state into a pseudo-potential interaction model to capture the physics of methane flow in irregular networks of channels that represent nano-scale porous media. We use atomistic simulations to calibrate and validate our model in slit nano-channels. We propose a preconditioning scheme to initialize the coupled transport and adsorption simulation of methane in complex porous media. The results of this implementation of LB agree with Direct Simulation Monte Carlo (DSMC) and Molecular Dynamics (MD) simulations. We then scale up the LB implementation through vectorization and indirect addressing. We parallelize it using Message Passing Interface (MPI) and OpenMP frameworks to simulate transport and adsorption in complex media with a million lattices. Additionally, we analyze the differences between coupled and transport-only simulations in two case studies and show that considering phase behavior, i.e., adsorption, can significantly change the flow behavior. This work constitutes an important step towards bridging the gap between molecular flow and system-scale behavior of complex disordered porous media.

42 ENGINEERING↗
DOE OSTI2020

A combined numerical and experimental study to elucidate primary breakup dynamics in liquid metal droplet-on-demand printing

Droplet-on-demand liquid metal jetting is emerging as a powerful technology for the additive manufacturing of metallic parts. The success of this method hinges on overcoming several technological challenges. Additionally, the principal one among these challenges is the controlled repeatable ejection of single uniform droplets. Due to the high density and surface tension of liquid metals, the droplet ejection process occurs near the minimal extremes of the printability phase diagram, defined by acceptable ranges for the Weber (We) and Ohnesorge (Oh) numbers. In this work, we experimentally demonstrate the satellite-free ejection of pneumatically actuated molten tin droplets in this extreme corner of printability and use a combination of high-speed video analysis and volume-of-fluid modeling to elucidate the droplet dynamics. While the simulations at low Oh and We can correctly describe several aspects of the breakup process, such as an increasing tail and pinch-point near the nozzle, no single parameter set can completely capture the droplet shape at breakup. Instead, the experimental droplet dynamics appear to include features from both high and low Oh breakup. This disagreement is ascribed to the incomplete description of the droplet ejection process including wetting and exit effects near the nozzle opening and surface effects such as transient cooling and oxide formation.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Data-driven, multi-moment fluid modeling of Landau damping

Deriving governing equations of complex physical systems based on first principles can be quite challenging when there are certain unknown terms and hidden physical mechanisms in the systems. In this work, we apply a deep learning architecture to learn fluid partial differential equations (PDEs) of a plasma system based on the data acquired from a fully kinetic model. Here, the learned multi-moment fluid PDEs are demonstrated to incorporate kinetic effect such as Landau damping. Based on the learned fluid closure, the data-driven, multi-moment fluid modeling can well reproduce all the physical quantities derived from the fully kinetic model. The calculated damping rate of Landau damping is consistent with both the fully kinetic simulation and the linear theory. The data-driven fluid modeling of PDEs for complex physical systems may be applied to improve the fluid closure and reduce the computational cost of multi-scale modeling of global systems.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

A Review of the Research and Development of Brayton Cycle Technology in Nuclear Power Applications with a Focus on Compressor Technology

This study reviews the integration of Brayton Cycle (BC) systems in nuclear power generation, emphasizing their potential to enhance thermal efficiency and operational flexibility over traditional Rankine Cycle (RC) systems. Key working fluids, such as helium (He), supercritical carbon dioxide (sCO 2 ), nitrogen (N 2 ), and air, are evaluated for their performance, efficiency, and compatibility with nuclear systems. He is recognized for its high thermal conductivity and inertness at elevated temperatures, while sCO 2 demonstrates advantages in compactness and efficiency in midrange temperatures. This article also highlights the importance of compressor designs in optimizing BC performance and reviews, available compressor technologies. Axial and centrifugal compressor designs enable efficient gas compression while managing the thermal and mechanical stresses associated with high-pressure operations in nuclear systems. Combined with variable geometry components and advanced materials, these technologies address the challenges posed by varying load conditions. Despite the promising features of BC systems, several challenges persist, including high leakage rates and material degradation under extreme conditions, which necessitate robust sealing technologies and thorough testing. The insights gained from operational experiences at facilities, such as the Oberhausen II plant and the High-Temperature He Test Facility (HHV), underscore the complexities involved in designing high-temperature gas turbines for nuclear applications. This review concludes that as the nuclear industry evolves, BC systems hold significant promise for contributing to a sustainable energy future, particularly in the context of small modular reactors (SMRs) and microreactors. Further exploration of combined cycle configurations that combine BCs with RCs may enhance overall efficiency and flexibility in power generation.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

An Update on Cardinal: Toward Full Core Pebble Simulations

The new DOE-NE Center of Excellence for Thermal-fluids applications in Nuclear Energy inaugurated in April 2018 considers and researches novel new solution strategies for historically challenging flow issues that still plague the current fleet of deployed Light Water nuclear Reactors (LWRs) as well as predicting various fluid flow and fluid related issues with advanced reactor technologies. Our advanced thermal-fluids research and development approach synergistically combines three natural, though overlapping, length and time scales in a hierarchal multi-scale approach to avoid the temptation and pitfalls of attempting to develop a single solve-all algorithm for physical fluid flow problems that will span nine orders of magnitude in spatial and temporal scales. To demonstrate the multi-scale philosophy of the center we focus on Fluoride Cooled High Temperature Reactors (FHRs), and in particular on the Berkley’s PB-FHR Mark-I design. The Fluoride salt cooled High temperature Reactor (FHR) is a class of advanced nuclear reactors that combine the robust coated particle fuel form from high temperature gas cooled reactors, direct reactor auxiliary cooling system (DRACS) passive decay removal of liquid metal fast reactors, and the transparent, high volumetric heat capacitance liquid Fluoride salt working fluids - such as Flibe - from molten salt reactors. This combination of fuel and coolant enables FHRs to operate in a high-temperature low-pressure design space that has beneficial safety and economic implications. The PB-FHR reactor relies on a pebble bed approach and pebble bed reactors are in a sense the poster child for multi-scale analysis. The lower length-scale simulator for pebble reactor cores comprises three physics: neutronics (OpenMC), thermal-fluids (Nek5000/NekRS) and fuel performance (BISON). As part of Center of Excellence ongoing research efforts we have developed Cardinal, a new tool platform for lower length-scale simulation. Cardinal tightly couples all three physics and leverages advances in MOOSE such as the MultiApp system and the concept of MOOSE-wrapped Apps. The present report provides an update on the development of Cardinal with an extension of Cardinal to GPUs. We also perform a first-of-a-kind demonstration simulation on Summit representing a 10x capability increase in terms of pebble count for Cardinal.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2020

Transient flow modeling in fractured media using graphs

In this work, we describe a method to simulate transient fluid flows in fractured media using an approach based on graph theory. Our approach builds on past work where the graph-based approach was successfully used to simulate steady-state fluid flows in fractured media. We find a mean computational speedup of the order of 1400 from an ensemble of a 100 discrete fracture networks in contrast to the O(10 4 ) speedup that was obtained for steady-state flows earlier. However, the transient flows considered here involve an additional degree of complexity that was not present in the steady-state flows considered previously with a graph-based approach, that of time marching and solution of the flow equations within a time-stepping scheme. We verify our method with an analytical test case and demonstrate its use on a practical problem related to fluid flows in hydraulically fractured reservoirs. By enabling the study of transient flows, we create an opportunity for a wide set of possibilities where a steady-state approximation is not sufficient, such as the example motivated by hydraulic fracturing that we present here. This work validates the concept that graphs are able to reliably capture the topological properties of the fracture network and serve as effective surrogates in an uncertainty-quantification framework.

58 GEOSCIENCES↗
DOE OSTI2022

Vorticity-induced flow-focusing leads to bubble entrainment in an inkjet printhead: Synchrotron x-ray and volume-of-fluid visualizations

The oscillatory flows present in an inkjet printhead can lead to strong deformations of the air-liquid interface at the nozzle exit. Such deformations may lead to an inward directed air jet with bubble pinch-off and the subsequent entrainment of an air bubble, which is highly detrimental to the stability of inkjet printing. Understanding the mechanisms of bubble entrainment is therefore crucial to improving print stability. Here, in the present work, we use ultrafast x-ray phase-contrast imaging and direct numerical simulations based on the volume-of-fluid method to study the mechanisms underlying the bubble entrainment in a piezoacoustic printhead. We first demonstrate good agreement between experiments and numerics. We then show the different classes of bubble pinch-off obtained in experiments, and that those were also captured numerically. The numerical results are then used to show that the baroclinic torque, which is generated at the gas-liquid interface due to the misalignment of density and pressure gradients, results in a flow-focusing effect that drives the formation of the air jet from which a bubble can pinch off.

42 ENGINEERING↗
DOE OSTI2024

Using Hydrodynamic Similarity as a Verification Method for Impact Cratering Simulations in the FLAG Hydrocode

Hydrodynamic codes (hydrocodes) are common tools for modeling hypervelocity impacts to provide insight into the physical phenomenon. Hydrocodes can simulate impacts from micrometer to kilometer spatial scales and reach impact velocities difficult to achieve in experimental settings. However, numerical models are approximations, and demonstrating that a numerical method is capable of providing physical results for these models is essential. In this work, we employ a hydrocode verification technique that leverages hydrodynamic similarity, a mathematical property of the conservation equations of fluid mechanics that form the basis for hydrocode models. Using the FLAG hydrocode, we simulate aluminum (Al) and basalt projectiles and targets at spatial scales spanning 7 orders of magnitude (hundreds of micrometers to kilometers). These materials were chosen because Al-6061 is a common material in spacecraft and satellites and basalt is a useful approximation of rocky astronomical bodies. Our results show that hydrodynamic similarity holds for each material model used and across spatial scales. We show that under certain conditions hydrodynamic similarity can apply in the presence of gravity and that similarity does not hold in the presence of strength models. We conclude that the FLAG hydrocode preserves important mathematical properties of fluid dynamics in hypervelocity impacts of Al-6061 and basalt.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Modeling the small-scale deposition of snow onto structured Arctic sea ice during a MOSAiC storm using snowBedFoam 1.0.

The remoteness and extreme conditions of the Arctic make it a very difficult environment to investigate. In these polar regions covered by sea ice, the wind is relatively strong due to the absence of obstructions and redistributes a large part of the deposited snow mass, which complicates estimates for precipitation hardly distinguishable from blowing or drifting snow. Moreover, the snow mass balance in the sea ice system is still poorly understood, notably due to the complex structure of its surface. Quantitatively assessing the snow distribution on sea ice and its connection to the sea ice surface features is an important step to remove the snow mass balance uncertainties (i.e., snow transport contribution) in the Arctic environment. In this work we introduce snowBedFoam 1.0., a physics-based snow transport model implemented in the open-source fluid dynamics software OpenFOAM. We combine the numerical simulations with terrestrial laser scan observations of surface dynamics to simulate snow deposition in a MOSAiC (Multidisciplinary Drifting Observatory for the Study of Arctic Climate) sea ice domain with a complicated structure typical for pressure ridges. The results demonstrate that a large fraction of snow accumulates in their vicinity, which compares favorably against scanner measurements. However, the approximations imposed by the numerical framework, together with potential measurement errors (precipitation), give rise to quantitative inaccuracies, which should be addressed in future work. The modeling of snow distribution on sea ice should help to better constrain precipitation estimates and more generally assess and predict snow and ice dynamics in the Arctic.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Improvements of SAM Heat Transfer Models for Molten Salt-Cooled Pebble Bed Reactors

To support the development and utilization of the SAM code for molten salt-cooled pebble bed reactor safety analyses and licensing, selected improvements were made to the one-dimensional system-level heat transfer modeling in SAM with the goal of better capturing heat transfer phenomena specific to these designs. In consideration of molten salt as a coolant, new models were introduced to capture the enhanced radiative heat transfer that must be considered at the higher working temperatures. Radiative heat transfer is handled not only between two structural surfaces, but also in combination between the surfaces and the molten salt fluid, which has a higher opacity and absorption of radiative heat as compared to water. Several examples of analytical verification of the new radiative heat transfer methods are included in this report. Additionally, convective heat transfer correlations were selected from literature and included in SAM to account for the enhanced heat transfer expected in pebble bed geometry flows. These correlations are verified and demonstrated in the present work with a reference FHR example.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2023

Multiscale graph neural network autoencoders for interpretable scientific machine learning

The goal of this work is to address two limitations in autoencoder-based models: latent space interpretability and compatibility with unstructured meshes. This is accomplished here with the development of a novel graph neural network (GNN) autoencoding architecture with demonstrations on complex fluid flow applications. To address the first goal of interpretability, the GNN autoencoder achieves reduction in the number nodes in the encoding stage through an adaptive graph reduction procedure. Further, this reduction procedure essentially amounts to flowfieldconditioned node sampling and sensor identification, and produces interpretable latent graph representations tailored to the flowfield reconstruction task in the form of so-called masked fields. These masked fields allow the user to (a) visualize where in physical space a given latent graph is active, and (b) interpret the time-evolution of the latent graph connectivity in accordance with the time-evolution of unsteady flow features (e.g. recirculation zones, shear layers) in the domain. To address the goal of unstructured mesh compatibility, the autoencoding architecture utilizes a series of multi-scale message passing (MMP) layers, each of which models information exchange among node neighborhoods at various lengthscales. The MMP layer, which augments standard single-scale message passing with learnable coarsening operations, allows the decoder to more efficiently reconstruct the flowfield from the identified regions in the masked fields. Analysis of latent graphs produced by the autoencoder for various model settings are conducted using unstructured snapshot data sourced from large-eddy simulations in a backward-facing step (BFS) flow configuration with an OpenFOAM-based flow solver at high Reynolds numbers.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Learning Physically Interpretable Atmospheric Models From Data With WSINDy

The multiscale and turbulent nature of Earth's atmosphere has historically rendered accurate weather modeling a hard problem. Recently, there has been an explosion of interest surrounding data-driven approaches to weather modeling, which in many cases show improved forecasting accuracy and computational efficiency when compared to traditional methods. However, many of the current data-driven approaches employ highly parameterized neural networks, often resulting in uninterpretable models and limited gains in scientific understanding. In this work, we address the interpretability problem by explicitly discovering partial differential equations governing atmospheric phenomena, identifying symbolic mathematical models with direct physical interpretations. The purpose of this paper is to demonstrate that, in particular, the weak-form sparse identification of nonlinear dynamics (WSINDy) algorithm can learn effective atmospheric models from both simulated and assimilated data. Our approach adapts the standard WSINDy algorithm to work with high-dimensional fluid data of arbitrary spatial dimension.

58 GEOSCIENCES↗