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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Evaluation of accuracy and convergence of numerical coupling approaches for poroelasticity benchmark problems

Accurate modeling of subsurface flow and transport processes is vital as the prevalence of subsurface activities such as carbon sequestration, geothermal recovery, and nuclear waste disposal increases. Computational modeling of these problems leverages poroelasticity theory, which describes coupled fluid flow and mechanical deformation. Although fully coupled monolithic schemes are accurate for coupled problems, they can demand significant computational resources for large problems. In this work, a fixed stress scheme is implemented into the Sandia Sierra Multiphysics toolkit. Two implementation methods, along with the fully coupled method, are verified with one-dimensional (1D) Terzaghi, 2D Mandel, and 3D Cryer sphere benchmark problems. The impact of a range of material parameters and convergence tolerances on numerical accuracy and efficiency was evaluated. Overall the fixed stress schemes achieved acceptable numerical accuracy and efficiency compared to the fully coupled scheme. However, the accuracy of the fixed stress scheme tends to decrease with low permeable cases, requiring the finer tolerance to achieve a desired numerical accuracy. For the fully coupled scheme, high numerical accuracy was observed in most of cases except a low permeability case where an order of magnitude finer tolerance was required for accurate results. Finally, a two-layer Terzaghi problem and an injection–production well system were used to demonstrate the applicability of findings from the benchmark problems for more realistic conditions over a range of permeability. Simulation results suggest that the fixed stress scheme provides accurate solutions for all cases considered with the proper adjustment of the tolerance. Furthermore, this work clearly demonstrates the robustness of the fixed stress scheme for coupled poroelastic problems, while a cautious selection of numerical tolerance may be required under certain conditions with low permeable materials.

58 GEOSCIENCES↗
NASA NTRS2018

Integrated Computational-Experimental Development of Lithium-Air Batteries for Electric Aircraft

The primary obstacle to enable NASA's vision of Green Aviation is the extraordinary energy storage requirements for electric aircraft. Significant advances in high energy, rechargeable, safe batteries are required to enable electric aviation. Boeing's SUGAR and NASA studies have identified 400 Wh/kg as the threshold energy density for general aviation and 750 Wh/kg for commercial regional air service. State of the Art Lithium Ion Battery (LIB) technology currently has a density of 200 Wh/kg and is expected to plateau at 300 Wh/kg due to fundamental chemistry limitations making it unsuitable for future electric aircraft. Additional demanding requirements include high power, rechargeability, and high safety. Such battery technology does not currently exist. The recent considerable activity in battery research (DOE, Tesla Gigafactory, etc) overwhelmingly has been geared towards reducing cost and improving safety of LIB technology in order to promote the adoption of electric automobiles; and thus it is expected to have little impact on electric aviation development. New battery materials will be needed for the "Beyond Li Ion" (BLI) technologies required for high energy, safe electric aviation. Li-Air batteries have the highest known theoretical energy density (3400 Wh/kg) and therefore and if realized promises to transform the global transportation system. These high energy batteries have the potential to meet the energy storage challenges of current and future NASA aeronautics and space missions in addition to many terrestrial transportation applications as well. However, this technology requires significant components development and integration, as it is currently unable to achieve aircraft requirements. The objective of this project is to leverage modern computational materials methods combined with battery multiphysics tools to develop radically advanced compatible cathode and electrolyte materials, build several Li-Air cells, and flight-demonstrate the corresponding Li-Air battery packs. A significant problem for current Lithium-Air batteries is large scale decomposition of the battery electrolyte during operation leading to battery failure after a handful of charge/discharge cycles. Therefore, development of large scale, ultra-high energy, rechargeable, and safe Lithium-Air batteries require highly stable electrolytes that are resistant to decomposition under operating conditions. A NASA-based cross-organizational "dream team" of high-powered experts combined integrated supercomputer modeling, fundamental chemistry analysis, advanced material science, and battery cell development to tackle this very challenging, multidisciplinary problem. The ultimate goal for the team is to develop an integrated experimental/computational infrastructure to produce a reliable predictive capability for the selection of optimal components, their fabrication parameters, and "design rules" of novel cell components for advanced ultra-high energy batteries that can meet energy storage challenges of NASA missions and many terrestrial transportation applications.

Li-air battery↗
DOE OSTI2025

Exact signed distance fields using parallel Fast Sweeping Method

Signed distance fields are often used in multiphysics simulations to track material interfaces. We present a simple methodology based on the fast sweeping method to generate the exact signed distance from triangular meshes and linear paths on Cartesian grids. The methodology propagates the closest primitive to the boundary to the rest of the domain following the characteristics. A local upwind criterion is used to decide between the new and existing closest primitive at each grid point while capturing the correct sign of the global function. The methodology has optimal computational complexity and runs efficiently in distributed-memory architectures. We include 2D and 3D test cases along with a resolution study up to 0.512 trillion zones and 1,000 computer cores. The solution strategy can also be applied to other types of meshes or collections of primitives.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Critical Assemblies: Dragon Burst Assembly and Solution Assemblies

This work reviews the historical literature associated with the Dragon experiment and water boiler reactors operated at Los Alamos during the Manhattan Project. Frisch’s invited talk given at the American Nuclear Society’s Fast Burst Reactor Conference held at the University of New Mexico in Albuquerque, New Mexico, in 1969 is quoted. From the literature review, basic models for the Dragon experiment and for a water boiler–type assembly (aqueous homogeneous reactor) were created that can be used for conducting multiphysics simulations for criticality excursion studies. This methodology utilizes the coupled neutronic-hydrodynamic method to perform a time-dependent dynamic simulation of a criticality excursion. MCNP® was utilized to calculate important nuclear kinetic parameters that were incorporated into the models. Simulation results compare reasonably well with historic data.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

Reactor physics benchmark experiments at the JSI TRIGA MARK II reactor - Current status and future outlook

Full text of publication follows. With the development of new high-fidelity computational methods, improvement of nuclear data, and multiphysics modelling, there is an increased need for benchmark experiments to experimentally validate the models, methods and input data. Many of the nuclear facilities designed to perform reactor physics benchmark experiments have been shut down. Therefore, research reactors offer a great opportunity for benchmark experiments, if they are well designed and performed with great care and accuracy. In this presentation we provide an overview of the past and ongoing activities related to benchmark experiments at the Jozef Stefan Institute TRIGA Mark II research reactor. The following experiments have been performed: criticality with fresh fuel, {sup 197}Au(n,γ) and {sup 27}Al(n,α) reaction rates in irradiation channels, absolute and relative {sup 197}Au(n,γ), {sup 235}U(n,f) and {sup 238}U(n,f) reaction rates in the core, burnup, kinetic parameters, control rod worth, isothermal reactivity coefficient, self-shielding, slow and fast (pulse) transients, nuclear heating, delayed and prompt gamma ray production, temperature profiles for multi-physics. Since the existing fleet of research reactors is ageing very rapidly and new experiments are needed, new research reactors should be designed and built to meet the needs of future advanced reactors, education and training, and other technologies in the coming years. We will review planned activities at the JSI TRIGA reactors and plans for the new research reactor in Slovenia. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2021

Predictive Data-driven Platform for Subsurface Energy Production

Subsurface energy activities such as unconventional resource recovery, enhanced geothermal energy systems, and geologic carbon storage require fast and reliable methods to account for complex, multiphysical processes in heterogeneous fractured and porous media. Although reservoir simulation is considered the industry standard for simulating these subsurface systems with injection and/or extraction operations, reservoir simulation requires spatio-temporal “Big Data” into the simulation model, which is typically a major challenge during model development and computational phase. In this work, we developed and applied various deep neural network-based approaches to (1) process multiscale image segmentation, (2) generate ensemble members of drainage networks, flow channels, and porous media using deep convolutional generative adversarial network, (3) construct multiple hybrid neural networks such as convolutional LSTM and convolutional neural network-LSTM to develop fast and accurate reduced order models for shale gas extraction, and (4) physics-informed neural network and deep Q-learning for flow and energy production. We hypothesized that physicsbased machine learning/deep learning can overcome the shortcomings of traditional machine learning methods where data-driven models have faltered beyond the data and physical conditions used for training and validation. We improved and developed novel approaches to demonstrate that physics-based ML can allow us to incorporate physical constraints (e.g., scientific domain knowledge) into ML framework. Outcomes of this project will be readily applicable for many energy and national security problems that are particularly defined by multiscale features and network systems.

58 GEOSCIENCES↗
DOE OSTI2021

Deployment of the Finite Volume Method in Pronghorn for Gas and Salt cooled Pebble Bed Reactors

This report summarizes the activities related to ”Complete FHR and HTGR pebble bed simulator, including initial validation” funded by the NEAMS thermal-hydraulics focus area. The activity revolves around the coarse-mesh thermal-hydraulics code Pronghorn and its application to gas and salt cooled Pebble bed reactor (PBR). The main difference between gas and salt cooled PBR from a thermal-hydraulics perspective is the fluid. To address the difference in fluid behavior, two separate approaches are implemented in the MOOSE Navier Stokes module: 1) a Boussinesq approximation and 2) a fully compressible formulation. The developed finite volume method capabilities are used for improving pre-existing gas-cooled and salt-cooled pebble-bed reactor models. A steady-state, multiphysics gas-cooled pebble-bed reactor model is created that couples the equilibrium core depletion capability developed in previous work, and the finite volume method capability developed for this report. The salt-cooled pebble-bed reactor model is upgraded to use the incompressible finite volume method capability and then extended to three spatial dimensions. Finally, several verification-and-validation exercises performed with Pronghorn are documented using the verification-and-validation report of the MooseDoc system. The goal of this effort to document the verification-and-validation level of Pronghorn and improve stakeholder confidence in the results obtained with Pronghorn.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

$χ$-$MeRA$: Computationally efficient adaptive mesh refinement of Monte Carlo mesh based tallies

Here, the reactor physics community is always focused on reducing the computational time and memory required for simulations. $χ$-$MeRA$, which stands for flux-based-($χ$)-Mesh tally Refinement Adaptively, was built to reduce the computational time and memory required to solve the neutronics side of a multiphysics problem when compared to traditional methods for mesh based tallies in Monte Carlo (MC) simulations. $χ$-$MeRA$ couples a MC code with an adaptive mesh refinement (AMR) algorithm to take advantage of the accuracy of a MC code and the efficiency of an AMR algorithm. Also developed within $χ$-$MeRA$ was a set of metrics to assess the effects of the refinement on various parameters in the simulation space. For a plutonium sphere, $χ$-$MeRA$ shows a reduction in memory usage and computation time when compared to a fully refined mesh by a factor of 14.7 and 6.7, respectively. When compared to an unstructured mesh, improvement of 1.3 and 4.8 was achieved for memory usage and computation time. The development of $χ$-$MeRA$ helps solve the neutronics side of a multiphysics problem in a faster, more computationally efficient manner than traditional methods, and the final mesh created contains accurate results that can be passed onto the next physics code.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Performance of explicit and IMEX MRI multirate methods on complex reactive flow problems within modern parallel adaptive structured grid frameworks

Large-scale multiphysics simulations are computationally challenging due to the coupling of multiple processes with widely disparate time scales. The advent of exascale computing systems exacerbates these challenges since these systems enable ever-increasing size and complexity. In recent years, there has been renewed interest in developing multirate methods as a means to handle the large range of time scales, as these methods may afford greater accuracy and efficiency than more traditional approaches of using implicit-explicit (IMEX) and low-order operator splitting schemes. However, to date there have been few performance studies that compare different classes of multirate integrators on complex application problems. In this work, we study the performance of several newly developed multirate infinitesimal (MRI) methods, implemented in the SUNDIALS solver package, on two reacting flow model problems built on structured mesh frameworks. The first model revisits prior work on a compressible reacting flow problem with complex chemistry that is implemented using BoxLib but where we now include comparisons between a new explicit MRI scheme with the multirate spectral deferred correction (SDC) methods in the original paper. The second problem uses the same complex chemistry as the first problem, combined with a simplified flow model, but runs at a large spatial scale where explicit methods become infeasible due to stability constraints. Two recently developed IMEX MRI multirate methods are tested. These methods rely on advanced features of the AMReX framework on which the model is built, such as multilevel grids and multilevel preconditioners. The results from these two problems show that MRI multirate methods can offer significant performance benefits on complex multiphysics application problems and that these methods may be combined with advanced spatial discretization to compound the advantages of both.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Statistical Distributions for Mesh Independent Solutions in ALEGRA

The representation of material heterogeneity (also referred to as "spatial variation") plays a key role in the material failure simulation method used in ALEGRA. ALEGRA is an arbitrary Lagrangian-Eulerian shock and multiphysics code developed at Sandia National Laboratories and contains several methods for incorporating spatial variation into simulations. A desirable property of a spatial variation method is that it should produce consistent stochastic behavior regardless of the mesh used (a property referred to as "mesh independence"). However, mesh dependence has been reported using the Weibull distribution with ALEGRA's spatial variation method. This report describes efforts towards providing additional insight into both the theory and numerical experiments investigating such mesh dependence. In particular, we have implemented a discrete minimum order statistic model with properties that are theoretically mesh independent.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Initial study on cross section generation requirements for a PBR equilibrium core

A Serpent model of the HTR-PM equilibrium core was developed for use in cross section prepa-ration studies in order to guide methods development for the Griffin reactor multiphysics applica-tion. The model includes detailed isotopics for 10 distinct pebble burnup groups in 126 core zoneswith unique fuel and moderator temperatures obtained from a coupled neutronics-thermal-fluidsequilibrium core calculation using Griffin-Pronghorn. A sensitivity study of the fuel and mod-erator temperatures for various core regions was performed with the MOOSE stochastic tools.The results show that the uncertainties are, not unexpectedly, dominated by the value of the fluidtemperature and that the power level, heat transfer coefficient and effective conduction to neigh-boring pebbles and fluid constitute, at best, second order effects. The temperature uncertaintyrange varies from 28 K to 57 K at the core entry and exit planes, respectively, but these val-ues are probably higher. We still have to quantify the significance of these uncertainties in thepreparation of cross sections, which will be postponed for future work. In addition, we verifythat the single effective pebble approach works well for the preparation of region averaged crosssections in the infinite domain approximation. Nevertheless, there are significant discrepanciesin the cross sections when compared to the multi-pebble model. This could affect the predictionof peak values and in the depletion calculation. We conclude that is highly desirable for futurestudies with Griffin to be able to handle both the ?effective? pebble approximation and the multi-pebble approach for the various pebble burnup groups. This enables Griffin users the flexibilityto perform higher-fidelity studies. Finally, we initiate the preparation of cross sections for variouscore regions from the full core Serpent reference model. We quantify the differences in 26 groupcross sections from infinite domain models. These reference cross sections will serve to validatethe double heterogeneity, self-shielding, and spectrum-correction methods in Griffin.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Initial study on cross-section generation requirements for a PBR equilibrium core

A Serpent model of the equilibrium core HTR-PM small modular nuclear reactor in China, was developed for use in cross-section preparation studies in order to guide methods development for the Griffin reactor multiphysics application. The model includes detailed isotopics for 10 distinct pebble burnup groups in 126 core zones with unique fuel and moderator temperatures obtained from a coupled neutronics-thermal-fluids equilibrium core calculation using Griffin-Pronghorn. A sensitivity study of the fuel and moderator temperatures for various core regions was performed with the MOOSE stochastic tools. The results show that the uncertainties are, not unexpectedly, dominated by the value of the fluid temperature and that the power level, heat transfer coefficient and effective conduction to neighboring pebbles and fluid constitute, at best, second order effects. The temperature uncertainty range varies from 28 K to 57 K between the core entry and exit planes, respectively, but these values are probably higher. We still have to quantify the significance of these uncertainties in the preparation of cross-sections in future work. In addition, we verified that the effective pebble approximation used in the PEBBED and V.S.O.P. computer codes works well for the preparation of region averaged cross-sections. Nevertheless, there are some discrepancies in the cross-sections when compared to the multi-pebble model, which could affect the prediction of peak values and the depletion calculation. We conclude that is highly desirable for future studies with Griffin to be able to handle both the 'effective' pebble approximation and the multi-pebble approach for various pebble burnup groups. This enables Griffin users with the flexibility to perform higher-fidelity studies. Finally, we initiated the preparation of cross-sections for various core regions from the full core Serpent reference model. We quantified the differences in 26 group cross-sections from infinite domain models versus the full core approach. These reference cross-sections will serve to verify the double heterogeneity, self-shielding, and spectrum-correction methods in Griffin. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2024

An analysis of parameters affecting ampacity in aircraft bipolar MVDC power cables via coupled electrical, thermal, and computational fluid dynamic modelling

Abstract The next generation of aircraft, including more electric aircraft and all‐electric aircraft (AEA), requires electric power systems with high power density and low system mass specifications. Increasing the voltage of the system to the range of a few kV, medium voltage (MV), is a reasonable approach to achieving high‐power‐density and low‐system‐mass EPSs for aircraft applications. Higher voltages, however, pose many challenges for aviation MV power cables such as arcs and arc tracking, partial discharges (PDs), and thermal management. In this regard, thermal management is more challenging since heat transfer by convection is greatly reduced at wide‐body aircraft's cruising altitudes due to the reduced air pressure. In this paper, a finite element method (FEM) model is developed in COMSOL Multiphysics for an aircraft bipolar MVDC (±5 kV) power cable. Using the model, the maximum permissible cable current at a low pressure of 18.8 kPa (at an altitude of 12.2 km from sea level, the usual cruising altitude for wide‐body aircraft) is calculated. Also, an analytical model is developed based on analytical and proven empirical correlations governing conductive, radiative, and convective heat transfers at the steady state to estimate the ampacity of the bipolar cable system at reduced pressure. It was shown that the proposed analytical model can be used for atmospheric pressure and systems with a larger number of poles, expanding its range of applications. The results of the FEM and analytical models correlate at wide ranges of parameters such as ambient temperature, duct size, distance between the positive and negative pole cables, and the overall diameter of the cables. The influence of horizontal and vertical arrangement of poles is included in the analytical model. The results of this study can be used to design bipolar MVDC power cable systems for the envisaged wide‐body AEA.

Azizi, Arian↗
DOE OSTI2024

Numerical modelling of impact seismic sources using the stress glut theory

SUMMARY Meteorite impacts have proved to be a significant source of seismic signal on the Moon, and have now been recorded on Mars by InSight seismometers. Understanding how impacts produce seismic signal is key to the interpretation of this unique data, and to improve their identification in continuous seismic records. Here, we use the seismic Representation Theorem, and particularly the stress glut theory, to model the seismic motion resulting from impact cratering. The source is described by equivalent forces, some resulting from the impactor momentum transfer, and others from the stress glut, which represents the mechanical effect of plasticity and non linear processes in the source region. We condense these equivalent forces into a point-source with a time-varying single force and nine-component moment tensor. This analytical representation bridges the gap between the complex dynamics of crater formation, and the linear point-source representation classically used in seismology. Using the multiphysics modelling software HOSS, we develop a method to compute the stress glut of an impact, and the associated point-source from hypervelocity impact simulations. For a vertical and an oblique impact at 1000 m s−1, we show that the moment tensor presents a significant deviatoric component. Hence, the source is not an ideal isotropic explosion contrary to previous assumptions, and draws closer to a double couple for the oblique impact. The contribution of the point force to the seismic signal appears negligible. We verify this model by comparing two signals: (1) HOSS is coupled to SPECFEM3D to propagate the near-source signal elastically to remote seismic stations; (2) the point-source model derived from the stress-glut theory is used to generate displacements at the same distance. The comparison shows that the point-source model is accurately simulating the low-frequency impact seismic waveform, and its seismic moment is in trend with Lunar and Martian impact data. High-frequencies discrepancies exist, which are partly related to finite-source effects, but might be further explained by the difference in mathematical framework between classical seismology and HOSS’ numerical modelling.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Development of a Method for Shape Optimization for a Gas Turbine Fuel Injector Design Using Metal-Additive Manufacturing

Adjoint shape optimization has enabled physics-based optimal designs for aerodynamic surfaces. Additive manufacturing (AM) makes it possible to manufacture complex shapes. However, there has been a gap between optimal and manufacturable surfaces due to the inherent limitations of commercial computational fluid dynamics (CFD) codes to implement geometric constraints during adjoint computation. In such cases, the design sensitivities are exported and used to perform constrained shape modifications using parametric information stored in computer aided design (CAD) files to satisfy manufacturability constraints. However, modifying the design using adjoint methods in CFD solvers and performing constrained shape modification in CAD can lead to inconsistencies due to different shape parameterization schemes. This paper describes a method to enable the simultaneous optimization of the fluid domain and impose AM manufacturability constraints, resolving one of the key issues of geometry definition for isogeometric analysis. Similar to a grid convergence study, the proposed method verifies the consistencies between shape parameterization techniques present within commercial CAD and CFD software during mesh movement as a part of the adjoint shape optimization routine. By identifying the appropriate parameters essential to a shape optimization study, the error metric between the different parameterization techniques converges to demonstrate sufficient consistencies for justifiable exchange of data between CAD and CFD. For the identified shape optimization parameters, the error metric to measure the deviation between the two parameterization schemes lies within the AM laser-powder bed fusion (L-PBF) process tolerance. Additionally, comparison for subsequent objective function calculations between iterations of the optimization loop showed acceptable differences within 1% variation between the modified geometries obtained using the two parameterization schemes. This method provides justification for the use of multiphysics guided adjoint design sensitivities computed in CFD software to perform shape modifications in CAD to incorporate AM manufacturability constraints during the shape optimization loop such that optimal designs are also additively manufacturable.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

Volcanic arc rigidity variations illuminated by coseismic deformation of the 2011 Tohoku-oki M9

Rock strength has long been linked to lithospheric deformation and seismicity. However, independent constraints on the related elastic heterogeneity are missing, yet could provide key information for solid Earth dynamics. Using coseismic Global Navigation Satellite Systems (GNSS) data for the 2011 M9 Tohoku-oki earthquake in Japan, we apply an inverse method to infer elastic structure and fault slip simultaneously. We find compliant material beneath the volcanic arc and in the mantle wedge within the partial melt generation zone inferred to lie above ~100 km slab depth. We also identify low-rigidity material closer to the trench matching seismicity patterns, likely associated with accretionary wedge structure. Along with traditional seismic and electromagnetic methods, our approach opens up avenues for multiphysics inversions. Those have the potential to advance earthquake and volcano science, and in particular once expanded to InSAR type constraints, may lead to a better understanding of transient lithospheric deformation across scales.

58 GEOSCIENCES↗
NASA NTRS2018

Coupled Radiative Thermal and Nonlinear Stress Analysis for Thermal Deformation in Large Space Structures

Large space structures are capable of large thermal deformations in the space environment. A case of large-scale thermal deformation was observed in the analysis of the Near Earth Asteroid Scout solar sail, with predicted tip displacements of more than one meter in seven-meter booms. Experimental data supports the broad conclusions of the analysis, but shows poor agreement on the details of the thermal deformation. Prediction that is precise enough to drive engineering decisions will require coupled thermal-stress analysis with features that are not found in current multiphysics codes. This paper describes a simple method for stepwise coupling between commercial nonlinear stress analysis software and radiative thermal analysis software. Results are presented for a round stainless steel tube, which is a common case in existing literature.

Stohlman, Olive R.↗
DOE OSTI2024

Accelerating Thermochemical Equilibrium Calculations for Nuclear Reactor Applications

Thermochemical properties play a key role in modeling and simulation of several key phenomena in nuclear reactors. There has been an increasing interest in incorporating CALPHAD-based formulations in multiphysics simulations including for Molten Salt Reactors where knowledge of phase evolution of the salt and the chemical potentials of various elements are of utmost importance in source term analyses and redox control. However, the size of such simulations is often limited by the high computational cost of full thermodynamic equilibrium calculations. This work discusses the current efforts aimed at accelerating thermochemical equilibrium calculations for multiphysics simulations performed using the open-source finite element / finite volume code Multiphysics Object Oriented Simulation Environment (MOOSE) [1]. While several methods have been proposed for accelerating phase equilibrium calculations [2], most focus on relatively small systems and often rely on a- priori knowledge of the state-space of the system. Nuclear materials, however, are often multi-component systems owing to the evolution of composition under irradiation and an approach based on a-priori mapping of phase diagram is often not enough. This work is aimed at demonstrating an on-the-fly surrogate modeling framework that uses active learning to reduce the number of full equilibrium calculations that must be performed. By combining with efficient coupling approaches, the surrogate framework helps in reducing the computational cost of thermodynamic equilibrium informed multiphysics simulations of nuclear materials. The performance is benchmarked against full coupling with the thermochemistry library Thermochimica [3]. This work uses a machine learning based approach for constructing surrogate models to predict the stable phases in a multicomponent system. The surrogates were constructed using neural networks and Gaussian process classification. In this work, we compare the relative performance of the two methods. We also demonstrate the use of caching previous calculations by interpolating the values from nearest neighbors. References [1] Lindsay, A.D., et al. "2.0 – MOOSE: Enabling massively parallel multiphysics simulation", SoftwareX, 20 (2022): 101202. [2] Roos, W.A. and Zietsman J.H. "Accelerating complex chemical equilibrium calculations – A Review", Calphad, 77 (2022): 102380. [3] Piro, M.H.A., et al. "The thermochemistry library Thermochimica", Computational Materials Science, 67 (2013): 266-272.

36 MATERIALS SCIENCE↗