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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 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Modeling Flow in a Microreactor Core: From High-Fidelity CFD to Subchannel Analysis

The accurate prediction of pressure drop in tightly packed, low–Reynolds number (Re) bare rod bundles is essential for the thermal-hydraulic design of the Microreactor Applications Research Validation and EvaLuation (MARVEL) reactor and other microreactor concepts. However, existing friction factor correlations, particularly the upgraded Cheng-Todreas (UCTD) correlation, have limited validation for the small pitch-to-diameter ratios (P/Ds) and transitional flow conditions characteristic of these systems. In this work, we perform high-fidelity large-eddy simulations (LESs) of both an infinite bare rod bundle and a finite bare 37-pin scalloped rod bundle across the range 1000≤ 𝑅𝑒 ≤5500. The simulations reveal strong gap vortex–driven transitional behavior and indicate that the UCTD may underpredict the friction factor by up to 28% at 𝑃/𝐷 = 1.05. Using the LES-calculated pressure drops, we formulate a new friction factor correlation that follows the Cheng-Todreas functional form but is calibrated for low-Re and tightly packed geometries representative of a MARVEL-like reactor. The correlation is implemented in the MOOSE (Multiphysics Object-Oriented Simulation Environment) subchannel module and compared against both the LES and UCTD predictions. Across all subchannel types, the proposed model reduces the streamwise velocity differences from as high as 44% (UCTD) to below 9%, and decreases the pressure gradient differences from 13% to 25% (UCTD) to 0.7% to 7% relative to the LES results. These results suggest that the new correlation has the potential to improve the pressure drop and flow field predictions for such geometries, highlighting the importance of high-fidelity simulations in supporting microreactor thermal-hydraulic model development and motivating future pressure drop experiments for compact rod bundles to further validate these findings.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗
DOE OSTI2020

Aerotaxy: gas-phase epitaxy of quasi 1D nanostructures

Cost- and resource-efficient growth is necessary for many applications of semiconductor nanowires. We here present the design, operational details and theory behind Aerotaxy, a scalable alternative technology for producing quality crystalline nanowires at a remarkably high growth rate and throughput. Using size-controlled Au seed particles and organometallic precursors, Aerotaxy can produce nanowires with perfect crystallinity and controllable dimensions, and the method is suitable to meet industrial production requirements. Here, we explain why Aerotaxy is an efficient method for fabricating semiconductor nanowires and explain the technical aspects of our custom-built Aerotaxy system. Investigations using SEM (Scanning Electron Microscope), TEM (Transmission Electron Microscope)and other characterization methods are used to support the claim that Aerotaxy is indeed a scalable method capable of producing nanowires with reproducible properties. We have investigated both binary and ternary III–V semiconductor material systems like GaAs and GaAsP. In addition, common aspects of Aerotaxy nanowires deduced from experimental observations are used to validate the Aerotaxy growth model, based on a computational flow dynamics (CFD) approach. We compare the experimental results with the model behaviour to better understand Aerotaxy growth.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2025

Performance Analysis and Simulaion of the Hydraulic Scram System in TREAT Reactor

The Transient Reactor Test Facility (TREAT) at Idaho National Laboratory (INL) serves a vital role in nuclear fuel safety research, enabling transient experiments that simulate reactivity excursions and accident scenarios. Central to these operations is the transient control rod drive system (TCRDS), which drives rapid motion of the transient control rods such that TREAT can simulate rapid power changes typical of reactor accidents. The reliability and performance of this system are critical for protecting both fuel specimens and reactor infrastructure. This study presents the initial phase of a two-year investigation into the dynamics and reliability of the TREAT hydraulic TCRDS. Conducted in collaboration with INL, the research employs a combined computational and experimental approach to analyze the system's response time, pressure transients, and potential failure modes. Emphasis is placed on understanding how fluid characteristics influence the TCRDS’s ability to achieve both rapid power changes and mechanical stability. The TRDS and the skid that powers it will be analyzed throughout this investigation. Computational modeling using computational fluid dynamics (CFD) will simulate the hydraulic response under varying conditions. In parallel, experimental testing planned at INL will validate these models and capture key performance metrics. This paper outlines the system design, analytical framework, and modeling strategies that form the foundation for later testing. Ultimately, this work aims to support improvements to the TCRDS’s design and reliability, contributing to the broader goal of enhancing nuclear fuel safety and sustaining TREAT’s mission as a premier nuclear fuel test facility.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗
DOE OSTI2026

Insights into mixing of non-isothermal multi-polymer melts for complex plastics recycling

Catalytic recycling or upcycling of plastics is often limited not by catalyst performance, but by transport, arising from highly viscous, non-Newtonian polymer melts. In this work, we develop a reactor-scale framework that integrates rheological measurements, constitutive modeling, computational fluid dynamics (CFD), and experiments to quantify mixing, heat transfer, and dispersion in surrogate hydrocarbon melts representing mixed plastics systems. Temperature- and shear rate-dependent viscosity of low-density polyethylene (LDPE) and high-density polyethylene (HDPE) is measured to create two surrogate polymers (PLD and PHD) that capture the dominant shear-thinning flow behavior while neglecting strong elastic effects, enabling tractable simulation of non-isothermal, polymer-melt mixing using a Carreau-Arrhenius generalized Newtonian framework. Three-dimensional CFD simulations are employed to evaluate impeller performance in PLD using mixing time, cavern volume, thermal uniformity, and interfacial area for regimes in which viscoelastic effects are not dominant. We show that magnetic stir bars commonly used in lab-scale studies produce large thermal gradients (~60 °C) and poor mixing, even under idealized power delivery and polymer flow conditions. In contrast, close-clearance anchor impellers achieve near-isothermal operation, reduce mixing times by up to 5×, and provide >90% active circulation volume. We further demonstrate that, at low pseudo-Deborah number (De*), motor power requirements can be predicted directly from shear rate-dependent rheology using the Carreau-Arrhenius framework, enabling rational selection of operating conditions. Extension to surrogate immiscible multi-polymer systems based on PLD and PHD shows that interfacial area is highly sensitive to operating conditions and impeller design, with coaxial anchor-turbine configurations enhancing dispersion by up to 4 × .

Close-clearance impellers↗
DOE OSTI2025

Analysis of soot formation from aviation fuels in laminar counterflow flames

Combustion emissions from aviation contribute to the formation of condensation trail (contrail) that can lead to the formation of anthropogenic cirrus clouds. Ice particles that form contrails are observed to have a linear correlation with soot particle number density. Synthetic aviation fuels (SAFs) offer a promising route to mitigate the production of soot particles while also increasing energy security. Although studies have focused on combustion and spray behavior, the detailed investigation of soot formation processes for different jet fuels and their impact on models for computational fluid dynamics (CFD) applications is not well understood. Moreover, experimental measurements of soot for canonical flames using Synthetic aviation fuels (SAF) for model validation remain scarce. To address this, we use employed the Lawrence Livermore National Laboratory (LLNL) detailed soot model based on the discrete sectional method. Additionally, we develop two reduced chemical mechanisms for Jet-A and Alcohol-to-Jet (C1) that are suitable for turbulent flame simulations and couple them with the Hybrid Method of Moments (HMOM). The detailed and reduced model frameworks are validated against experimental measurements of soot volume fraction (ƒ ν ) from a counterflow burner experiment previously reported in the literature. Given the good agreement between modeling results and experimental measurements for the (1) spatial distribution of ƒ ν and (2) the non-linear variation of peak ƒ ν with strain rate, we further investigate the modeled sub-processes (nucleation, condensation, surface growth, and oxidation) using the LLNL model to analyze the assumptions in the reduced model framework. Furthermore, the results indicate a significant contribution from resonant radicals to the surface growth of soot particles, which are not accounted for in the current implementation of HMOM and could help reconcile soot predictions by the reduced model with observations.

Counterflow↗
DOE OSTI2023

Unconventional gas-phase preparation of the prototype polycyclic aromatic hydrocarbon naphthalene (C 10 H 8 ) via the reaction of benzyl (C 7 H 7 ) and propargyl (C 3 H 3 ) radicals coupled with hydrogen-atom assisted isomerization

Polycyclic aromatic hydrocarbons (PAHs) are ubiquitous in the interstellar medium and in meteorites such as Murchison and Allende and signify the missing link between resonantly stabilized free radicals and carbonaceous nanoparticles (soot particles, interstellar grains). However, the predicted lifetime of interstellar PAHs of some 108 years imply that PAHs should not exist in extraterrestrial environments suggesting that key mechanisms of their formation are elusive. Exploiting a microchemical reactor and coupling these data with computational fluid dynamics (CFD) simulations and kinetic modeling, we reveal through an isomer selective product detection that the reaction of the resonantly stabilized benzyl (C 7 H 7 ) and the propargyl (C 3 H 3 ) synthesizes the simplest representative of PAHs – the 10π Hückel aromatic naphthalene (C 10 H 8 ) molecule – via the novel Propargyl Addition–BenzAnnulation (PABA) mechanism. The gas-phase preparation of naphthalene affords a versatile concept of the reaction of combustion and astronomically abundant propargyl radicals with aromatic radicals carrying the radical center at the methylene moiety (aromatic-CH 2 ) as a previously passed over source of aromatics in high temperature environments thus bringing us closer to an understanding of the aromatic universe we live in.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

A PIC Bootstrapping Strategy for Exascale CFD-DEM Simulation

The exascale computing era comes with the release of MFIX-Exa, a new code for studying gas-particle fluidization using CFD-DEM and PIC models on massively parallel, heterogeneous high-performance computing architectures. However, as compute resources continue to grow in scale and complexity, so too does the impetus to use them efficiently. Here, we propose a novel bootstrapping method to minimize neglected simulation time and cast the approach more broadly among a growing field of multi-fidelity methods.

Porcu, Roberto↗
DOE OSTI2021

Benchmarking a Pronghorn Model of the Natural Convection Shutdown Heat Removal Test Facility Against STAR-CCM+ (Poster)

Summary Verification of Pronghorn’s Net Radiation Transfer via Code-to-Code comparison with STAR-CCM+. Comparison based on Natural Convection Shutdown Heat-Removal Test Facility (NSTF). Near-perfect agreement if conjugate heat transfer inside the riser channels is replaced by fixed temperature. Difference of up to 5K if conjugate heat transfer is modeled (correlation vs. full CFD).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Method for designing a combustion system with reduced environmentally-harmful emissions

A method for designing a combustion system which emits less of at least one environmentally-harmful emission is presented. In a describing step, an injector which introduces a fuel into a combustion chamber is described via a CFD code. In a modeling step, combustion kinetics of the fuel are modeled via a pre-processing code as the fuel mixes and reacts with an oxidizer. In a first selecting step, at least one primary scalar is derived during the modeling of the combustion kinetics. In a performing step, a table look-up is performed to obtain at least one data from a look-up database based on the primary scalar. In a second selecting step, at least one secondary scalar is selected in addition to the primary scalar(s). In a specifying step, at least one chemical pathway of formation or destruction for the secondary scalar is specified via a chemistry manager wherein the secondary scalar is representative of the environmentally-harmful emission(s) of the chemical pathway(s). In a utilizing step, the data is utilized to evaluate the chemical pathway(s) to quantify the environmentally-harmful emission(s). In an identifying step, an improvement to the combustion system is identified which reduces the environmentally-harmful emission(s).

Zambon, Andrea C.↗
DOE OSTI2024

Thermochemical Nonequilibrium Modeling in a Continuous-Galerkin, Finite-Element Framework

The presented work discusses the implementation, verification, and validation of Park's two-temperature model in a scalable, computational fluid dynamics (CFD) code developed at the US Department of Energy's Oak Ridge National Laboratory (ORNL). The implementation of Park's two-temperature model was verified through 0D test cases involving an adiabatic reactor and a nitrogen thermal bath. The implementation was then validated through comparisons with other validated CFD codes and experimental data on a hypersonic cylinder and double cones. These are standard benchmark test cases for thermochemical non-equilibrium (TCNE) modeling, and all data are shared publicly. The verification and validation results showed that ORNL's in-house CFD code could model complex, high-speed flow problems with and without TCNE modeling. This work is essential for future research involving 3D shock wave/boundary layer interactions (SBLIs).

Nutter, Nicole↗
DOE OSTI2024

Implementation of Detailed Polyethylene Pyrolysis Kinetics into CFD Simulations using Machine Learning

Municipal solid waste (MSW) and waste plastics have received significant attention due to the issues of waste generation and storage, as well as their potential as an energy resource. High-density polyethylene (HDPE) makes up a large portion of plastic waste and has been the subject of several conversion studies. However, the mechanisms associated with converting HDPE through pyrolysis and gasification are extensive and complex making them difficult to implement into high-fidelity computational fluid dynamic (CFD) simulations. For this project, a primary pyrolysis mechanism containing 42 unique species and 737 heterogeneous reactions was used to generate kinetic data over a range of operating conditions. A machine learning (ML) model was developed to replicate the results of the detailed pyrolysis mechanism while significantly increasing the computational efficiency. A deep operator network (DeepONet) architecture was adopted to train the model using time steps relevant to CFD simulations. The ML used physics-based loss functions to ensure mass conservation. The ML model has been deployed in simple MFiX CFD simulations, single particle, and an experimental drop tube reactor, and has shown promising performance compared to the original scheme.

Houston, Ross↗
DOE OSTI2022

Validation of NEAMS Tools Using MSRE Data

This report documents the benchmarks developed and performed for the tools and codes developed under the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program utilizing the MSRE experiment data. There are three focus areas explored in this work: fuel evolution, CFD, and system transient analyses. Fuel depletion is important for MSR reactor physics and fuel cycle analysis. Fuel depletion capability is currently being developed in the Griffin reactor physics code. To support this, a benchmark problem is developed using the MSRE data and an existing depletion code with flowing fuel analysis functionality (ADDER) to validate this new capability in Griffin. The ADDER calculation is compared with the TRITON-MSR results as well as the MSRE experimental data. This benchmark can be directly used to verify and validate the Griffin fuel depletion capability in future years. For CFD simulation, the MSRE CAD model is obtained from the Copenhagen Atomics and a mesh is generated for the MSRE inlet plenum. The Nek5000 code will be employed to find the flow distribution in the MSRE inlet plenum based on the mesh generated. For system analysis, a simple benchmark problem for three types of MSR system transients is developed. The SAM and SPECTRA codes are used to solve the simple problem, and the results from the two codes agree well. The SAM code is also employed to obtain the frequency response of the MSRE system at the 5 and 8 MWt power levels. The results agree well with the experiment measurements. These verification and validation efforts gives SAM users more confidence in MSR system transient simulations using SAM. Lastly, the SAM-Griffin Multiphysics coupling work is initiated. A simple one-way coupling of evaluating the precursor drift effect on the MSRE k-eff is demonstrated. This preliminary coupling work serves as the basis for future more complex Multiphysics simulation and modelling.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Computational Study on the Effect of Thermal Boundary Conditions and Axial Aspect Ratio on Catalytic Oxidative Coupling of Methane

Packed-bed reactor models with a large reactor-diameter-to-particle-diameter ratio (N > 10) are commonly used in catalysis research. Their use is underpinned by strong simplifying assumptions including unidirectional plug flow, negligible radial gradients, small axial diffusion, and isothermal operation. However, the complex exothermic–endothermic nature of reactions like oxidative coupling of methane (OCM) coupled with heat transfer from the catalyst surface and convective heat losses from the reactor wall provides an interesting case study to evaluate packed-bed assumptions and understand axial and radial temperature variations that may impact conversion and selectivity. This computational study investigates the effect of thermal boundary conditions on catalyst performance in laboratory OCM reactors (N = ~13) through computational fluid dynamics (CFD) simulation. Further, the 1-D model typically used for modeling plug flow reactors assumes negligible radial temperature and species concentration gradients. This assumption is evaluated for OCM reactors over a range of geometric axial aspect ratios, defined as the reactor length divided by the diameter, comparing the 1-D with 3-D CFD results. 1-D model predictions of catalyst performance start to deviate from the 3-D model predictions as the axial aspect ratio decreases, specifically as diameter increases at constant length. In the work, the 1-D model assumption is only found to be valid for axial aspect ratios higher than 1.6, a result considered to be relevant for all exothermic catalytic reactors.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

A reduced-order model of concentration polarization in reverse osmosis systems with feed spacers

Feed spacers in reverse osmosis systems generate complex fluid flows that limit computational fluid dynamics (CFD) simulations to small length and time scales. That limits our ability to simulate mineral scaling and other membrane fouling phenomena, which occur over longer length and time scales. Thus motivated, we develop a reduced model that replaces the CFD simulation of the velocity field with an analytical model that mimics spacers. This focuses the remaining numerical effort on simulating the advection–diffusion equation governing solute transport. We motivate and validate the model with CFD simulations and bench-scale experiments of spacer filaments in three different arrangements, including cases of unsteady vortex shedding. We show that the model produces a roughly 10,000-fold speedup compared to CFD, and accurately reproduces CFD predictions of not only the average and maximum concentrations, but also the local concentration distribution along the membrane. Here, we also demonstrate the model for simulating a feed channel with a length-to-height ratio of 200. The model provides a simple testbed for exploratory studies of multispecies transport, precipitation, and membrane fouling phenomena for which simulating spacers is often prohibitive.

Computational fluid dynamics↗
DOE OSTI2021

Application of NEAMS Codes to Capture MSR Phenomena

This report documents work completed in FY21 under the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program’s Molten Salt Reactor (MSR) Application Drivers activity at Argonne. The common focus was on identifying the modeling and simulation functional requirements for designing, licensing, and operating MSRs and applying those capabilities already developed in NEAMS tools to example problems of interest. The four main parts of this report each focuses on a specific area of simulation physics as it relates to MSR phenomena: fuel evolution, chemistry, computational fluid dynamics (CFD), and systems analysis. In terms of fuel evolution, which includes depletion, decay, on-line separations, and transmutation, the current state of computational capabilities for modeling this behavior in liquid-fueled molten salt reactor is discussed. Some of the functional requirements to accomplish the various applications of MSR fuel depletion modeling are highlighted, followed by a summary of recent approaches and code development activities. The chemistry functional requirements were discussed in the context of several applications of high importance for MSRs, such as corrosion, salt chemistry, and species transport. Each of these types of chemistry modeling have considerable impact on various aspects of reactor applications, including informing on reactor designs, improving operational efficiencies, analyzing safety and reactivity concerns, and estimating the mechanistic source term of the reactor. A brief overview is also provided on code development activities ongoing under NEAMS relevant to chemistry modeling of MSRs. In terms of CFD applications, the state-of-the-art spectral element code, Nek5000 was used to model the fluid dynamics within a full core of the Molten Salt Fast Reactor (MSFR) concept designed as part of the Euratom EVOL project. This concept was selected as the challenge problem because of its similar features to several U.S. industry concepts. The goal was to model some of the fast MSR design challenges, including potential large internal re-circulations, the need of accurate tracking of delayed neutron precursors (DNP), and the lack of relevant thermal-hydraulics models/correlations, etc. Therefore, a series of CFD models were created for the MSFR core cavity using a k – τ model two-equation model for the turbulence. These first full core results demonstrated that any potential recirculation zones could be properly identified with the current NEAMS CFD capabilities. The development of these models will also set the stage for future testing of Nek5000’s functionalities to model other MSR thermal-fluid phenomena. Lastly, the validation of SAM against experimental data from the Molten Salt Reactor Experiment, which started in FY19, continues with the inclusion of modeling the reactivity insertion tests. This involved using SAM and its point kinetics model for flowing fuel salt to recreate the time dependent power changes and response after positive reactivity insertions at the 1, 5, and 8 MWt power levels. Through these exercises, several code modifications were suggested to the SAM development team and accommodated to enable closer agreement with solid technical and physical justifications. These include adding a moderator reactivity feedback coefficient as an available input and modifying the solution approach for the point kinetics model. Additional SAM development suggestions for flowing fuel MSRs include adding the capability to allow the moderator power change proportionally with the reactor power and enabling specification of the power and DNP distributions separately.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2020

Multidimensional modeling of non-equilibrium plasma generated by a radio-frequency corona discharge

Low-temperature plasma (LTP) ignition concepts rely on the production of radical and charged species to speed up the onset of combustion in spark-ignition engines. These features are responsible for the superior performance of LTP igniters under extremely dilute combustion operation that is not achievable by conventional spark igniters. Additionally, LTP discharges extend the lifetime of the igniters, due to the avoidance of spark processes. For these reasons, the engine research community and the automotive industry have shown growing interest in this technology in the recent years. As of today, computational fluid-dynamics (CFD) codes typically used by the multi-dimensional engine modeling community do not have reliable models to describe LTP ignition processes. One key missing piece of information is the physical and chemical properties of the plasma and their effect on combustion ignition. Most non-equilibrium plasma simulations reported in literature are based on simplified, canonical geometries, with simple discharge excitation schemes. Here we conduct multi-dimensional modeling of the non-equilibrium plasma generated by an application-relevant radio-frequency (RF) corona discharge in air. Three test cases are simulated, characterized by different environmental pressure levels and peak electrode voltage values at room temperature. Streamer penetration, electron number density, atomic oxygen production, and bulk gas temperature distribution in the first 10 sinusoidal pulses are presented and discussed. This model can be used as a key tool for an in-depth understanding of RF-corona discharge for automotive applications and provides the basis for future implementations of dedicated LTP ignition models in CFD codes.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Thermal Modelling of Advanced Test Reactor Fuel in a Generalized Dry Storage System

Star-CCM+, a computational fluid dynamics (CFD) software was used to conduct modeling and simulation of the thermal performance of a dry storage configuration consisting of Department of Energy Standardized Canisters (DOESCs) loaded with aluminum-clad spent nuclear fuel (ASNF.) The configuration includes nine DOESCs loaded with Advanced Test Reactor ASNF contained within a stainless steel overcanister centered in a ventilated, concrete overpack. The simulations were used to estimate the maximum temperatures reached by backfill gases inside the overcanister and DOESCs.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

A physics-constrained neural ordinary differential equations approach for robust learning of stiff chemical kinetics

The high computational cost associated with solving for detailed chemistry poses a significant challenge for predictive computational fluid dynamics (CFD) simulations of turbulent reacting flows. While deep learning techniques have been explored to develop faster surrogate models, they often fail to integrate reliably with CFD solvers. This instability arises because traditional deep learning approaches optimize for training error without ensuring compatibility with ordinary differential equation (ODE) solvers, resulting in accumulation of errors over time. Recently, neuralODE (NODE) based approaches have been shown to be a promising technique to emulate and accelerate detailed chemistry computations. Here, in the present work, we extend this NODE framework for stiff chemical kinetics by incorporating mass conservation constraints directly into the loss function during training. This ensures that the total mass as well as the individual elemental species masses are conserved in an a-posteriori manner. Proof-of-concept studies are performed with the novel physics-constrained NODE (PC-NODE) approach for homogeneous autoignition of hydrogen-air mixture over a range of composition and thermodynamic conditions. It is demonstrated that the PC-NODE framework not only improves the physical consistency of the resulting data-driven model with respect to mass conservation criteria, but also improves training efficiency. PC-NODE is shown to achieve 2–100× speedup relative to the hydrogen-air detailed chemical mechanism depending on the type of the ODE solver (implicit or explicit) used during autoregressive inference tests. Lastly, a-posteriori studies are performed wherein the trained PC-NODE model is coupled with a CFD solver. It is shown that higher accuracy is achieved with PC-NODE relative to the purely data-driven NODE approach. Moreover, PC-NODE also exhibits robustness and generalizability to unseen initial conditions from within (interpolative capability) as well as outside (extrapolative capability) the training regime.

computational combustion↗