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At least 451 records · Page 25

Off-Design Analysis of Axisymmetric External-Compression Supersonic Inlets for Mach 1.4 to 2.0

Supersonic axisymmetric, external-compression inlets designed for freestream Mach numbers of Mach 1.4, 1.7, and 2.0 were evaluated to characterize their off-design performance. The inlets were characterized as isolated from the airframe with freestream conditions, engine-face geometry, and flow rates established from a reference NASA commercial aircraft concept. The off-design performance was characterized using computational fluid dynamics (CFD) simulations. The study characterized the off-design performance at the cruise condition for variations in the inlet flow rate, angle-of-attack, and freestream Mach number. Also characterized was the inlet performance at take-off and approach-to-landing conditions for which the use of auxiliary intakes was included. The inlet performance was characterized by the flow rates, total pressure recovery and distortion, and drag. An understanding of the off-design performance of the axisymmetric inlets provides information for the selection of inlets for commercial supersonic aircraft.

Supersonic Inlets↗

Off-Design Analysis of Axisymmetric External-Compression Supersonic Inlets for Mach 1.4 to 2.0

Supersonic axisymmetric, external-compression inlets designed for freestream Mach numbers of Mach 1.4, 1.7, and 2.0 were evaluated to characterize their off-design performance. The inlets were characterized as isolated from the airframe with freestream conditions, engine-face geometry, and flow rates established from a reference NASA commercial aircraft concept. The off-design performance was characterized using computational fluid dynamics (CFD) simulations. The study characterized the off-design performance at the cruise condition for variations in the inlet flow rate, angle-of-attack, and freestream Mach number. Also characterized was the inlet performance at take-off and approach-to-landing conditions for which the use of auxiliary intakes was included. The inlet performance was characterized by the flow rates, total pressure recovery and distortion, and drag. An understanding of the off-design performance of the axisymmetric inlets provides information for the selection of inlets for commercial supersonic aircraft.

Supersonic Inlets↗

System Identification Applied to Dynamic CFD Simulation and Wind Tunnel Data

Demanding aerodynamic modeling requirements for military and civilian aircraft have provided impetus for researchers to improve computational and experimental techniques. Model validation is a key component for these research endeavors so this study is an initial effort to extend conventional time history comparisons by comparing model parameter estimates and their standard errors using system identification methods. An aerodynamic model of an aircraft performing one-degree-of-freedom roll oscillatory motion about its body axes is developed. The model includes linear aerodynamics and deficiency function parameters characterizing an unsteady effect. For estimation of unknown parameters two techniques, harmonic analysis and two-step linear regression, were applied to roll-oscillatory wind tunnel data and to computational fluid dynamics (CFD) simulated data. The model used for this study is a highly swept wing unmanned aerial combat vehicle. Differences in response prediction, parameters estimates, and standard errors are compared and discussed

Murphy, Patrick C.↗

Intermediate scattering functions of a rigid body monoclonal antibody protein in solution studied by dissipative particle dynamic simulation

In the past decade, there was increased research interest in studying internal motions of flexible proteins in solution using Neutron Spin Echo (NSE) as NSE can simultaneously probe the dynamics at the length and time scales comparable to protein domain motions. However, the collective intermediate scattering function (ISF) measured by NSE has the contributions from translational, rotational, and internal motions, which are rather complicated to be separated. Widely used NSE theories to interpret experimental data usually assume that the translational and rotational motions of a rigid particle are decoupled and independent to each other. To evaluate the accuracy of this approximation for monoclonal antibody (mAb) proteins in solution, dissipative particle dynamic computer simulation is used here to simulate a rigid-body mAb for up to about 200 ns. The total ISF together with the ISFs due to only the translational and rotational motions as well as their corresponding effective diffusion coefficients is calculated. The aforementioned approximation introduces appreciable errors to the calculated effective diffusion coefficients and the ISFs. For the effective diffusion coefficient, the error introduced by this approximation can be as large as about 10% even though the overall agreement is considered reasonable. Thus, we need to be cautious when interpreting the data with a small signal change. In addition, the accuracy of the calculated ISFs due to the finite computer simulation time is also discussed.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Analysis of Launch Vehicle Liftoff Debris: Historical Perspective from Space Shuttle and Application to Artemis I

Human exploration-class launch vehicles are inherently prone to debris due to the extreme environments generated during pre-launch operations, liftoff, and flight. The use of cryogenic propellants often requires thermal protection system (TPS) coatings, typically foam, to maintain the propellant conditions in the tank and prevent an accumulation ice on the external surface of the vehicle. Some ice growth is to be expected at umbilical interfaces, vents, flanges, or brackets where it is difficult to apply TPS. This ice may come loose at any time due to wind on the launch pad, structural vibration and acoustics after rocket ignition, or aerodynamic forces during flight. This phenomena is especially apparent on vehicles with no TPS, such as the Saturn V rockets used in the Apollo Program, see Figure 1. During propellant tanking, the thermal contraction of the underlying substrate may generate cracks in the TPS (Figure 1). Chunks of TPS can release due to the expansion of ingested gas from cryopumping or from aerodynamic forces if the crack creates an offset surface. Most foams will also have a certain amount of “popcorning” where small pieces of foam will pop off during flight because of the differential between the static surface pressure and the pressure of the gas trapped in the foam cell structure. There are a number of other coating or closeout materials that may be shed from the vehicle and become debris. During pre-launch operations and liftoff, the vehicle may also be exposed to debris originating from the launch pad or ground support equipment. This debris is separate from foreign object debris, or FOD, which is not intended to be present and is strictly controlled through operations and maintenance procedures. In this case, debris is generated from hardware and materials that are necessary for launch and are subject to the intense vibration, acoustics, and direct plume impingement of the launch environment. Examples include ice from umbilicals, tape and tie wraps that protect cables, and rust or corrosion from the launch platform. While NASA has historically been aware of debris as a potential issue that could cause a failure resulting in loss of mission, loss of vehicle, or loss of crew, the likelihood and severity of that risk was not always well understood or given sufficient weight in program and flight decisions. After the Space Shuttle Columbia accident (STS-107), the investigation found that foam TPS debris shed from the external tank was the proximate cause of the damage to the orbiter wing. Six previous observations of debris released from the foam ramp that covered the bipod connecting the forward end of the orbiter to the external tank resulted in minor changes or were determined to be accepted flight risks. Two occurrences of bipod ramp foam loss were not identified until the STS-107 investigation. Despite the damage inflicted by these debris strikes, the Shuttle Program Requirements Control Board deemed the vehicle safe to fly. During the Return to Flight effort following the Columbia disaster, NASA Engineering developed a process for the assessment of debris transport, impact, and damage tolerance to support independent assessments of risk by NASA Safety and Mission Assurance (S&MA). Under this system, each element (vehicle or ground system) defines a catalog of all expected debris based on launch history, component testing, or analysis. Debris transport analysis (DTA) is conducted using the debris catalog characteristics and potential flow transport mechanisms (e.g., vehicle aerodynamics, gravity, wind, plume-driven). The predicted debris impact locations and velocities are provided to the hardware owners, who use available test data and analysis to determine whether each component can withstand the impacts. In cases where the element hardware may be severely damaged or fail, the options are to mitigate the debris source through some change in design or operation, or to work with S&MA to try to characterize the probability of the impact and damage for program risk acceptance. Because of the differences in debris characteristics and transport, the DTA has been divided between the Liftoff and Ascent regimes. The development and application of Liftoff DTA methodology from the Shuttle Program to the current Artemis Program is the subject of this paper. Liftoff DTA covers the time from the start of pre-launch operations at the launch pad, up until the vehicle clears the launch tower and there is no longer any interaction with ground systems. Debris transport during this period is broadly classified as either gravity, wind, and plume-entrained (GWPE) or plume driven (PD). GWPE debris is generally lower speed, travelling in a forward-to-aft direction. PD transport includes flow features from the rocket ignition transient, as well as plume impingement and recirculation that occur as the vehicle lifts off the launch platform. In these cases, the debris typically moves in an aft-to-forward direction at higher speeds. The applicable transport mechanisms must be considered for each piece of debris depending on the material, and release location and time. For example, rust or metallic debris from the tower could fall (GWPE) and impact the vehicle before landing on the launch platform deck where it could be also be transported by plume impingement (PD). However, falling ice (GWPE) from an umbilical is unlikely to survive impact with the vehicle or launch platform and be available for PD transport. Modeling of debris transport is accomplished using a set of DTA tools which simulate debris trajectories subject to a reference frame acceleration (i.e., gravity) and aerodynamic drag. Where the trajectory encounters a solid surface, the debris is allowed to rebound with a specified coefficient of restitution. The drag is calculated by interpolating the fluid state at each point in the debris trajectory from high-fidelity computational fluid dynamics (CFD) simulations of the launch vehicle and pad. The CFD data may either be static (steady state or time averaged), typically for GWPE transport, or dynamic (time-accurate) for PD flow features like the ignition transient. Examples of the CFD flow field solutions for the Space Launch System (SLS) rocket and launch pad are shown in Figure 2. Typical SLS debris trajectory predictions from DTA are illustrated in Figure 3. The final version of this paper will include a more detailed examination of the Liftoff DTA process developed during the Shuttle Program, and how it has been augmented and applied to the SLS rocket under the Artemis Program. Comparisons with debris observations from the Artemis I launch will demonstrate validation of the tools and methodology.

Debris↗

Prediction of local concentration fields in porous media with chemical reaction using a multi scale convolutional neural network

The study of solute transport in porous media is of interest in many chemical engineering systems. Some example applications include packed bed catalytic reactors, filtration devices, and batteries. The pore scale modeling of these systems is time consuming and may require large computing resources, for this reason computational fluid dynamics (CFD) simulations are not practical if a large number of simulations is required, like in multiscale modeling, where a model at a large scale calls for pore scale simulations. It has been shown that neural networks can be trained with a dataset of flow simulations and then predict fields orders of magnitude faster, and with less computational resources, in new domains. However, it is crucial to provide the neural network with an effective description of the domain and the undergoing operating conditions to be able to train models that generalize accurately in unseen samples. Therefore, research is needed to employ neural networks in new complex systems. The appropriate training of a network for predicting coupled flow and solute transport processes is an outstanding problem due to the complex interplay between geometry and operating conditions. In this work, we train a multi scale convolutional neural network (MSNet) with a diverse dataset of simulations of transport and chemical reaction in porous media to predict the local concentration fields in images of porous media. Our dataset contains a wide diversity of sphere pack arrangements under different operating conditions (Péclet and Reynolds numbers). Further, we train a robust model by employing different input descriptors that represent the medium and the different operating conditions of each system. Our trained model is able to provide nearly instantaneous predictions, compared to around twenty hours of the CFD workflow, with less than 3.5% error on new geometries and transport conditions. Thus the model could be easily integrated in a multiscale workflow where fast response is needed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A Multidisciplinary Modeling Approach of Plant Gas Exchange in Reduced Gravity Environments

In-situ food production is a necessary step for human exploration of the solar system and requires a deep understanding of plant growth in reduced gravity environments. In particular, the lack of buoyancy-driven convection changes the gas exchange at the leaf surface, which decreases photosynthesis and transpiration rates, and ultimately biomass production. To understand the intricate relations between physical, chemical, and biochemical processes, the following methodology combines the development of a mechanistic model of plant growth in reduced gravity environments, computational fluid dynamics (CFD) simulations, and experiments in different time frames.The model presented here is a coupled mass and energy balance using the single round leaf assumption, including gravity as an entry parameter, and the leaf surface temperature as an output variable. Measures of the leaf surface temperature using infra-red cameras allow for a computation of the transpiration rate. This approach was followed to design a parabolic flight experiment, which performed 7 flights, and enabled data collection for model validation in different gravity and ventilation settings on a short time frame. Current measures of carbon assimilation and transpiration rate at the leaf and canopy level using an infra-red gas analyzer (Li-6800) in 1g lab conditions on several species will enable a validation on longer time frames and further calibration of the model. CFD studies both on the parabolic flight and on the lab experimental set-up allow the precise assessment of ventilation above the canopy and plants' leaves.Ultimately, this work will provide recommendations for the design of future plant growth hardware, especially on the lowest adequate ventilation for optimal plant growth in reduced gravity environments, as well as assessing biomass and oxygen production rates on planetary surfaces and space stations. This work was funded by CNES, CNRS, Clermont Auvergne Metropole, and NASA Space Biology through NASA postdoctoral program / USRA.

Poulet, Lucie↗

NASA ERA Integrated CFD for Wind Tunnel Testing of Hybrid Wing-Body Configuration

NASAs Environmentally Responsible Aviation (ERA) Project explores enabling technologies to reduce aviations impact on the environment. One research challenge area for the project has been to study advanced airframe and engine integration concepts to reduce community noise and fuel burn. In order to achieve this, complex wind tunnel experiments at both the NASA Langley Research Centers (LaRC) 14x22 and the Ames Research Centers 40x80 low-speed wind tunnel facilities were conducted on a Boeing Hybrid Wing Body (HWB) configuration. These wind tunnel tests entailed various entries to evaluate the propulsion airframe interference effects including aerodynamic performance and aeroacoustics. In order to assist these tests in producing high quality data with minimal hardware interference, extensive Computational Fluid Dynamic (CFD) simulations were performed for everything from sting design and placement for both the wing body and powered ejector nacelle systems to the placement of aeroacoustic arrays to minimize its impact on the vehicles aerodynamics. This paper will provide a high level summary of the CFD simulations that NASA performed in support of the model integration hardware design as well as some simulation guideline development based on post-test aerodynamic data. In addition, the paper includes details on how multiple CFD codes (OVERFLOW, STAR-CCM+, USM3D, and FUN3D) were efficiently used to provide timely insight into the wind tunnel experimental setup and execution.

Computational Fluid Dynamics↗

NASA ERA Integrated CFD for Wind Tunnel Testing of Hybrid Wing-Body Configuration

The NASA Environmentally Responsible Aviation (ERA) Project explored enabling technologies to reduce impact of aviation on the environment. One project research challenge area was the study of advanced airframe and engine integration concepts to reduce community noise and fuel burn. To address this challenge, complex wind tunnel experiments at both the NASA Langley Research Center's (LaRC) 14'x22' and the Ames Research Center's 40'x80' low-speed wind tunnel facilities were conducted on a BOEING Hybrid Wing Body (HWB) configuration. These wind tunnel tests entailed various entries to evaluate the propulsion-airframe interference effects, including aerodynamic performance and aeroacoustics. In order to assist these tests in producing high quality data with minimal hardware interference, extensive Computational Fluid Dynamic (CFD) simulations were performed for everything from sting design and placement for both the wing body and powered ejector nacelle systems to the placement of aeroacoustic arrays to minimize its impact on vehicle aerodynamics. This paper presents a high-level summary of the CFD simulations that NASA performed in support of the model integration hardware design as well as the development of some CFD simulation guidelines based on post-test aerodynamic data. In addition, the paper includes details on how multiple CFD codes (OVERFLOW, STAR-CCM+, USM3D, and FUN3D) were efficiently used to provide timely insight into the wind tunnel experimental setup and execution.

Computational Fluid Dynamics↗

Computational Methods for HSCT-Inlet Controls/CFD Interdisciplinary Research

A program aimed at facilitating the use of computational fluid dynamics (CFD) simulations by the controls discipline is presented. The objective is to reduce the development time and cost for propulsion system controls by using CFD simulations to obtain high-fidelity system models for control design and as numerical test beds for control system testing and validation. An interdisciplinary team has been formed to develop analytical and computational tools in three discipline areas: controls, CFD, and computational technology. The controls effort has focused on specifying requirements for an interface between the controls specialist and CFD simulations and a new method for extracting linear, reduced-order control models from CFD simulations. Existing CFD codes are being modified to permit time accurate execution and provide realistic boundary conditions for controls studies. Parallel processing and distributed computing techniques, along with existing system integration software, are being used to reduce CFD execution times and to support the development of an integrated analysis/design system. This paper describes: the initial application for the technology being developed, the high speed civil transport (HSCT) inlet control problem; activities being pursued in each discipline area; and a prototype analysis/design system in place for interactive operation and visualization of a time-accurate HSCT-inlet simulation.

Cole, Gary L.↗

Multiscale Experiments and Multiphysics Simulation of Multiphase Flow for Transportable Small Modular Reactors

A new type of safe, small, transportable nuclear reactor would address the intense and ever-growing global demand for energy produced via a resilient, carbon-free energy source. In this regard, transportable small modular reactors (SMRs) are being designed and developed for electricity generation within small/micro-grid/off-grid isolated systems, as well as for heat generation in industrial/residential applications. These reactors feature the capability to be fully factory fabricated and then directly transported to utilities’ sites as “plug-and-play” systems. Research and development (R&D) programs are underway at Idaho National Laboratory (INL) to successfully design, develop, and demonstrate such safe-by-design mobile reactor technologies, in collaboration with partner organizations. Multiscale experimental facilities and multiphysics simulation tools are required for reactor design verification and validation (V&V), and licensing. These advanced reactors are intended to feature passive safety systems such as passive containment cooling systems (PCCS), which consist of multiphase flows and multispecies distributions. This seminar talk will focus on designing and analyzing transportable SMR PCCS by using multiscale experiments and multiphysics computational fluid dynamics (CFD) simulations to support reactor licensing and safety. The corresponding research challenges are addressed via supportive verification and validation results generated by the models and simulation tools in combination with selective parametric and uncertainty analysis. This solution approach could blaze the trail for commercial adoption of such technologies. The facilities, simulation capabilities, and research opportunities available at INL in regard to such reactors and the integrated energy systems with which they go hand in hand are also discussed briefly, and may spark interest in deeper research as well as new collaborative projects.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Development of the Planar Inlet Design and Analysis Process (PINDAP)

The aerodynamic development of an engine inlet requires a comprehensive program of both wind tunnel testing and Computational Fluid Dynamics (CFD) simulations. To save time and resources, much "testing" is done using CFD before any design ever enters a wind tunnel. The focus of my project this summer is on CFD analysis tool development. In particular, I am working to further develop the capabilities of the Planar Inlet Design and Analysis Process (PINDAP). "PINDAP" is a collection of computational tools that allow for efficient and accurate design and analysis of the aerodynamics about and through inlets that can make use of a planar (two-dimensional or axisymmetric) geometric and flow assumption. PINDAP utilizes the WIND CFD flow solver, which is capable of simulating the turbulent, compressible flow field. My project this summer is a continuation of work that I performed for two previous summers. Two years ago, I used basic features of the PINDAP to design a Mach 5 hypersonic scramjet engine inlet and to demonstrate the feasibility of the PINDAP. The following summer, I worked to develop its geometry and grid generation capabilities to include subsonic and supersonic inlets, complete bodies and cowls, conic leading and trailing edges, as well as airfoils. These additions allowed for much more design flexibility when using the program.

Gruber, Christopher R.↗

Leveraging Large Eddy Simulations to Characterize Aeroacoustic Environments on Launch Vehicles

NASA's Space Launch System (SLS) program has relied on multiple wind tunnel campaigns to predict expected aeroacoustic environments. Time, cost, Reynolds number matching, contamination from test section acoustics, and limitations in spatial resolution are all factors that impact the use experimental data for development of launch vehicle environments. Methodological and computational advances over the last decade are enabling scale resolving computational fluid dynamics (CFD) simulations to be completed that can address some the challenges with conventional datasets, enabling more complete/accurate modeling of dynamic loading events on ascent. These simulations are classified as so-called "Large-Eddy Simulations" (LES). As the name implies, these simulations seek to directly resolve the turbulence in the largest, most-energetic turbulent structures, or eddies, and the dissipation of the smallest eddies in the flow field, is modeled. Like anything else, these simulations still must undergo rigorous testing and validation for the results to ultimately be trusted in the analysis of a launch vehicle. EV33 has begun to conduct some of this early-stage testing and validation to better support NASA missions in the future.

Jonathan Boustani↗

Dynamic separation of gases using microsieves

Separation of light weight molecules, such as nitrogen, argon, and oxygen, from heavier compounds can have significant impacts on energy capture, environmental monitoring, or isotopic applications. Large-scale gas separation techniques, like gas centrifugation and membrane mitigation, can be problematic as they impart tremendous energy and induce high mechanical stress onto the instrumentation. Microsieves, also known as micronozzles or microfunnels, are developed to create physical barriers to separate specific isotopes and gases. Separation is achieved using a converging and diverging micronozzle to impose supersonic gas flow around a curved wall, and it has been used for the separation of heavy actinide isotopes in low weight gas as well as separation of low weight gas compositions of nitrogen and argon back in 1900s. However, systematic reviews of this unique technology are lacking. The application of the Laval style nozzle, which has a converging/diverging entrance fundamental to the micronozzle, is included in this review due to its importance in industrial applications in uranium (U) isotope refinement. Using advanced computational fluid dynamic (CFD) simulations, the extent of gas separation can be modelled. Herein, we first examine the literature and survey recent advances on fabrication techniques for creating curved micronozzles, methods and separation principles used to design devices. Furthermore, we then follow with highlights of CFD simulations applied to evaluate the separation effects using microsieves. Finally, identification of the gap and recommendation for future development and applications are suggested for using intrinsic molecular features and fluidic dynamics in formulating separation strategies.

30 Microfluidics↗

Aerobrake aerothermodynamic environment predictions in support of the Aeroassist Flight Experiment

A computational fluid dynamic (CFD) simulation of the flow past an Aeroassist Flight Experiment (AFE) aerobrake under wind tunnel test conditions has been made. The Navier-Stokes equations in three dimensions were solved numerically using a finite-volume, implicit approach. Comparisons with experimental data include surface pressures and heat transfer rates and aerodynamic coefficients. Agreement with experiment is shown to be excellent. The dependence of the solution on the computational grid is explored. The present work is preliminary to simulation of the flow past the AFE under flight conditions, which at present cannot be duplicated with ground-based experimental facilities.

Fay, John F.↗

Computational fluid dynamics at NASA Ames and the numerical aerodynamic simulation program

Computers are playing an increasingly important role in the field of aerodynamics such as that they now serve as a major complement to wind tunnels in aerospace research and development. Factors pacing advances in computational aerodynamics are identified, including the amount of computational power required to take the next major step in the discipline. The four main areas of computational aerodynamics research at NASA Ames Research Center which are directed toward extending the state of the art are identified and discussed. Example results obtained from approximate forms of the governing equations are presented and discussed, both in the context of levels of computer power required and the degree to which they either further the frontiers of research or apply to programs of practical importance. Finally, the Numerical Aerodynamic Simulation Program--with its 1988 target of achieving a sustained computational rate of 1 billion floating-point operations per second--is discussed in terms of its goals, status, and its projected effect on the future of computational aerodynamics.

Peterson, V. L.↗

Reduced-Order CFD Modeling to Support Waste Loading Optimization in Hanford WTP Vitrification

The U.S. DOE Hanford Site stores over 56 million gallons of radioactive liquid tank waste that must be treated and immobilized for long-term disposal The Waste Treatment and Immobilization Plant (WTP) will vitrify this waste by feeding it into Joule-heated melters, where it is incorporated into a stable borosilicate glass Computational fluid dynamics (CFD) simulations of glass melters can provide insight into the maximum achievable waste loading under varying melter operating conditions Fully resolved VOF multiphase simulations were used as the reference model to capture bubble-driven convection in the melter, including bubble formation, rise behavior, and induced glass melt circulation Effective bubble column diameter and rise velocity were extracted from the resolved simulations, compared with empirical correlations, and refit across relevant viscosity and gas flow rate conditions Explicit gas–liquid interface tracking was replaced with a single-phase momentum source term model, enabling faster steady-state CFD simulations while preserving the dominant hydrodynamic effects of bubbling New empirical correlations were developed for effective bubble column diameter and bubble rise velocity by fitting resolved simulation data across expected melter viscosity and gas flow rate ranges, providing improved inputs for the momentum source term model compared with existing literature correlations The momentum source term model reduced fluid-domain mesh size by 89% and achieved an 8.4× computational speedup relative to resolved bubbling simulations The validated momentum source term approach enables prediction of process-relevant heat transfer behavior in the integrated melter model, including heat transfer from the molten glass to the cold cap, plenum, refractory walls, and surrounding structural regions under varying melter operating conditions

12 - MGMT OF RADIOACTIVE AND NON-RADIOACTIVE WASTE↗

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↗