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All sourcesNASA NTRSDOE OSTI
NASA NTRS2021

Recent Advancements in Modeling and Simulation of Entry Systems at NASA

This paper describes recent development of modeling and simulation technologies for entry systems in support of NASA’s exploration missions. Mission-tailored research and development in modeling of entry systems occurs across the Agency (e.g., within the Orion and Mars 2020 Programs), however the aim of this paper is to discuss the broad, cross-mission research conducted by NASA’s Entry Systems Modeling (ESM) Project, which serves as the Agency’s only concerted effort toward advancing entry systems across a range of technical disciplines. Technology development in ESM is organized and prioritized from a system-level perspective, resulting in four broad technical areas of investment: (1) Predictive material modeling, (2) Shock layer kinetics and radiation, (3) Computational and experimental aerosciences, and (4) Guidance, navigation, and control. Investments in thermal protection material modeling are geared toward high-fidelity, predictive models capable of handling complex structures, with an eye toward optimizing design performance and quantifying thermal protection system reliability. New computational tools have been developed to characterize material properties and behavior at the microstructural level, and experimental techniques (molecular beam scattering, micro-computed tomography, among others) have been developed to measure material kinetics, morphology, and other parameters needed to inform and validate detailed simulations. Advancements have also been made in macrostructural simulation capability to enable 3-D system-scale calculations of material response with complex topological features, including differential recession of tile gaps. Research and development in the area of shock layer kinetics has focused on air and CO2-based atmospheres. Capacity and capability of the NASA Ames Electric Arc Shock Tube (EAST) have been expanded in recent years and analysis of resulting data has led to several improvements in kinetic models, while simultaneously reducing uncertainties associated with radiative heat transfer predictions. First-principles calculations of fundamental kinetic, thermodynamic, and transport data, along with state-specificmodels for non-equilibrium flow regimes, have also yielded new insights and have the potential to vastly improve model fidelity. Aerosciences is a very broad area of interest in entry systems, yet a number of important challenges are being addressed: Coupled fluid-structure simulations of parachute inflation and dynamics; Experimental and computational studies of vehicle dynamics; Multi-phase flow with dust particles to simulate entry environments at Mars during dust storms; Studies of roughness-induced heating augmentation relevant to tiled and woven thermal protection systems; and Advanced numerical methods to optimize computational analyses for desired accuracy versus cost. Guidance and control in the context of entry systems has focused on development of methods for multi-axis control (i.e. pitch and yaw, rather than bank angle alone) of spacecraft during entry and descent. With precision landing requirements driven by Mars human exploration goals, recent efforts have yielded 6-DOF models of multi-axis control with propulsive descent of both inflatable and rigid ellipsled-like architectures. Results for both configurations have demonstrated the ability to land within the 50-meter precision requirement demanded by Mars human exploration missions, while also reducing propellant requirements by enabling more efficient control through entry and descent. Ongoing research in GN&C is developing mechanical specifications for the systems and establishing engineering feasibility.

aerothermodynamics↗
NASA NTRS2019

Recent Advancements in Modeling and Simulation of Entry Systems at NASA

This paper describes recent development of modeling and simulation technologies for entry systems in support of NASA's exploration missions. Mission-tailored research and development in modeling of entry systems occurs across the Agency (e.g., within the Orion and Mars 2020 Programs), however the aim of this paper is to discuss the broad, cross-mission research conducted by NASA's Entry Systems Modeling (ESM) Project, which serves as the Agency's only concerted effort toward advancing entry systems across a range of technical disciplines. Technology development in ESM is organized and prioritized from a system-level perspective, resulting in four broad technical areas of investment: (1) Predictive material modeling, (2) Shock layer kinetics and radiation, (3) Computational and experimental aerosciences, and (4) Guidance, navigation, and control. Investments in thermal protection material modeling are geared toward high-fidelity, predictive models capable of handling complex structures, with an eye toward optimizing design performance and quantifying thermal protection system reliability. New computational tools have been developed to characterize material properties and behavior at the microstructural level, and experimental techniques (molecular beam scattering, micro-computed tomography, among others) have been developed to measure material kinetics, morphology, and other parameters needed to inform and validate detailed simulations. Advancements have also been made in macrostructural simulation capability to enable 3-D system-scale calculations of material response with complex topological features, including differential recession of tile gaps. Research and development in the area of shock layer kinetics has focused on air and CO2-based atmospheres. Capacity and capability of the NASA Ames Electric Arc Shock Tube (EAST) have been expanded in recent years and analysis of resulting data has led to several improvements in kinetic models, while simultaneously reducing uncertainties associated with radiative heat transfer predictions. First-principles calculations of fundamental kinetic, thermodynamic, and transport data, along with state-specific models for non-equilibrium flow regimes, have also yielded new insights and have the potential to vastly improve model fidelity. Aerosciences is a very broad area of interest in entry systems, yet a number of important challenges are being addressed: Coupled fluid-structure simulations of parachute inflation and dynamics; Experimental and computational studies of vehicle dynamics; Multi-phase flow with dust particles to simulate entry environments at Mars during dust storms; Studies of roughness-induced heating augmentation relevant to tiled and woven thermal protection systems; and Advanced numerical methods to optimize computational analyses for desired accuracy versus cost. Guidance and control in the context of entry systems has focused on development of methods for multi-axis control (i.e. pitch and yaw, rather than bank angle alone) of spacecraft during entry and descent. With precision landing requirements driven by Mars human exploration goals, recent efforts have yielded 6-DOF models of multi-axis control with propulsive descent of both inflatable and rigid ellipsled-like architectures.

Barnhardt, Michael D.↗
DOE OSTI2021

Simulations of ion heating due to ion-acoustic instabilities in presheaths

Particle-in-cell, direct simulation Monte Carlo simulations reveal that ion-acoustic instabilities excited in presheaths can cause significant ion heating. Ion-acoustic instabilities are excited by the ion flow toward a sheath when the neutral gas pressure is small enough and the electron temperature is large enough. A series of 1D simulations were conducted in which neutral plasma (electrons and ions) was uniformly sourced with an ion temperature of 0.026 eV and different electron temperatures (0.1 eV–50 eV). Ion heating was observed when the electron-to-ion temperature ratio exceeded the minimum value predicted by linear response theory to excite ion-acoustic instabilities at the sheath edge (T e /T i ≈ 28). When this threshold was exceeded, the temperature equilibration rate between ions and electrons rapidly increased near the sheath so that the local temperature ratio did not significantly exceed the threshold for instability. This resulted in significant ion heating near the sheath edge, which also extended back into the bulk plasma; presumably due to wave reflection from the sheath. Furthermore, this ion-acoustic wave heating mechanism was found to decrease for higher neutral pressures, where ion-neutral collisions damp the ion-acoustic waves and ion heating is instead dominated by inelastic collisions in the presheath.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Computational model development and validation of fuel dispersal phenomena

As the US nuclear industry is renewing efforts to extend the rod average burnup limits in existing pressurized water reactors, it becomes imperative to investigate the safety implications associated with high burnup fuel fragmentation and the potential dispersal of fragmented fuel into the reactor coolant system. Additionally, as there is a growing interest in transitioning to new nuclear fuel designs to accommodate higher fuel burnup levels, it becomes essential to conduct studies on fuel behavior during design basis accident scenarios, particularly during a postulated loss-of-coolant accident, in order to ensure the safe operation of light-water reactors. The present study develops a computational model to simulate the complex three-phase flow of the fuel dispersal phenomena that occur following a breach in the cladding, when the stream of solid fuel particles and carrier fission gas stream may interact with the surrounding liquid medium. Furthermore, the proposed framework considers the solid phase as discrete Lagrangian particles while the interpenetrating gas–liquid continuum is modeled using a Eulerian framework. The developed simulation framework is validated with experimental results performed in a separate-effect test facility by comparing predicted particle settlement locations with the experimental observations reported in the literature. Key highlights of this study include the interpretation of the high-pressure boundary conditions and the three-phase flow coupling strategy. Also discussed are the gas–liquid hydrodynamics and the behavior of particles as they are transported through the gas and liquid phases.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS2007

Automated Knowledge Discovery From Simulators

A computational method, SimLearn, has been devised to facilitate efficient knowledge discovery from simulators. Simulators are complex computer programs used in science and engineering to model diverse phenomena such as fluid flow, gravitational interactions, coupled mechanical systems, and nuclear, chemical, and biological processes. SimLearn uses active-learning techniques to efficiently address the "landscape characterization problem." In particular, SimLearn tries to determine which regions in "input space" lead to a given output from the simulator, where "input space" refers to an abstraction of all the variables going into the simulator, e.g., initial conditions, parameters, and interaction equations. Landscape characterization can be viewed as an attempt to invert the forward mapping of the simulator and recover the inputs that produce a particular output. Given that a single simulation run can take days or weeks to complete even on a large computing cluster, SimLearn attempts to reduce costs by reducing the number of simulations needed to effect discoveries. Unlike conventional data-mining methods that are applied to static predefined datasets, SimLearn involves an iterative process in which a most informative dataset is constructed dynamically by using the simulator as an oracle. On each iteration, the algorithm models the knowledge it has gained through previous simulation trials and then chooses which simulation trials to run next. Running these trials through the simulator produces new data in the form of input-output pairs. The overall process is embodied in an algorithm that combines support vector machines (SVMs) with active learning. SVMs use learning from examples (the examples are the input-output pairs generated by running the simulator) and a principle called maximum margin to derive predictors that generalize well to new inputs. In SimLearn, the SVM plays the role of modeling the knowledge that has been gained through previous simulation trials. Active learning is used to determine which new input points would be most informative if their output were known. The selected input points are run through the simulator to generate new information that can be used to refine the SVM. The process is then repeated. SimLearn carefully balances exploration (semi-randomly searching around the input space) versus exploitation (using the current state of knowledge to conduct a tightly focused search). During each iteration, SimLearn uses not one, but an ensemble of SVMs. Each SVM in the ensemble is characterized by different hyper-parameters that control various aspects of the learned predictor - for example, whether the predictor is constrained to be very smooth (nearby points in input space lead to similar output predictions) or whether the predictor is allowed to be "bumpy." The various SVMs will have different preferences about which input points they would like to run through the simulator next. SimLearn includes a formal mechanism for balancing the ensemble SVM preferences so that a single choice can be made for the next set of trials.

Burl, Michael↗
DOE OSTI2025

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

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

Geosciences↗
DOE OSTI2021

Connect the Dots: In Situ 4-D Seismic Monitoring of CO 2 Storage With Spatio-Temporal CNNs

4-D seismic imaging has been widely used in CO 2 sequestration projects to monitor the fluid flow in the volumetric subsurface region that is not sampled by wells. Ideally, real-time monitoring and near-future forecasting would provide site operators with great insights to understand the dynamics of the subsurface reservoir and assess any potential risks. However, due to obstacles such as high deployment cost, availability of acquisition equipment, exclusion zones around surface structures, only very sparse seismic imaging data can be obtained during monitoring. That leads to an unavoidable and growing knowledge gap over time. The operator needs to understand the fluid flow throughout the project lifetime and the seismic data are only available at a limited number of times. This is insufficient for understanding reservoir behavior. To overcome those challenges, we have developed spatio-temporal neural-network-based models that can produce high-fidelity interpolated or extrapolated images effectively and efficiently. Specifically, our models are built on an autoencoder, and incorporate the long short-term memory (LSTM) structure with a new loss function regularized by optical flow. We validate the performance of our models using real 4-D post-stack seismic imaging data acquired at the Sleipner CO 2 sequestration field. We employ two different strategies in evaluating our models. Numerically, we compare our models with different baseline approaches using classic pixel-based metrics. We also conduct a blind survey and collect a total of 20 responses from domain experts to evaluate the quality of data generated by our models. Finally, via both numerical and expert evaluation, we conclude that our models can produce high-quality 2-D/3-D seismic imaging data at a reasonable cost, offering the possibility of real-time monitoring or even near-future forecasting of the CO 2 storage reservoir.

4-D seismic imaging↗
NASA NTRSDate not supplied

Computational Modeling of Mars Retropropulsion Concepts in the Langley Unitary Plan Wind Tunnel

Future human Mars missions will require powered descent starting at supersonic conditions, something which has never been done before at Mars. Computational powered descent flowfield simulations have been completed at full-scale Mars conditions, but the available ground test data are not appropriate for calibrating computational uncertainties for aerodynamic interference on proposed Mars descent vehicles. A test will be conducted in the NASA Langley Unitary Plan Wind Tunnel to begin addressing powered descent aerodynamics risks for large-scale human Mars entry concepts and to identify gaps in computational predictive capabilities. This paper covers pre-test computational flowfield predictions of two different models derived from full-scale reference vehicles: a blunt low lift-to-drag vehicle and a more slender geometry. Calculations of the blunt model include variations in nozzle configuration: nozzle location, size, area ratio, and pointing direction. There exist some significant differences between solvers, but some general trends are observed from simulations of the blunt model. First, aerodynamic axial force from the heatshield decreases with increasing thrust due to expanding plume blockage. Second, nozzles that point along the model axis result in lower aerodynamic axial force compared to nozzles that have a radial thrust component. Finally, placing the nozzles further away from the model nose preserves more heatshield axial force with increasing thrust compared to nozzles that are closer to the nose. For the slender model, the axial force from the heatshield is similar to the non-blowing axial force regardless of thrust magnitude, due to the nozzle arrangement on the heatshield. Once the test is completed, direct comparisons between the computations and test data will be made to determine computational uncertainties in a wind tunnel environment, to identify gaps in predictive capabilities, and to inform planning for future ground and flight test programs for Mars powered descent vehicles.

Supersonic Retropropulsion↗
NASA NTRSDate not supplied

Numerical Simulation of Lean Blowout of Alternative Fuels in 7-element Lean Direct Injector

This research presents the result of numerically simulating 7-element swirl-venturi Lean Direct Injector (SV-LDI) lean blowout (LBO) experiments conducted at NASA Glenn Research Center in May of 2019. After simulating a cold flow case to confirm the pressure drop agrees well with the experiment, additional cases with two different fuels (an average jet fuel and a Gevo alcohol-to-jet fuel) from the National Jet Fuels Combustion Program (NJFCP) were computed to numerically determine the LBO condition. The procedure to approach the LBO follows the method used in the experiment where the air mass flow rate is gradually increased while the fuel supply is maintained. Transient history of global heat release rate as a function of air flow rate is presented, as well as temperature contours at different conditions to give a visual representation of the flame state. The Open National Combustion Code (OpenNCC) used in this research adopted reduced HyChem (Hybrid Chemistry) models along with k-LES turbulence model and a Lagrangian spray model that takes into account droplet internal temperature distribution affected by the shear force on the droplet surface. The transport equations and chemical reaction terms are integrated together to enhance conservation of chemical species that are especially important in the near LBO conditions. After showing the computed range of LBO agrees well with the experimental measurements, time averaged solutions of both fuels at their initial condition and at their limiting condition just before LBO are compared in detail to facilitate the understanding of LBO mechanism.

combustion↗
DOE OSTI2020

Computationally efficient evaluation of optimum homogeneous charge compression ignition operating range with accelerated multizone engine cycle simulation

The very intensive calculations necessary to define a performance map requiring evaluation of over a hundred individual operating points can be efficiently conducted with accelerated multizone for engine cycle simulation, leading to a definition of regions of acceptable and optimum homogeneous charge compression ignition operation. Accelerated multizone for engine cycle simulation has the virtue of enabling accurate evaluation of many operating conditions based on thermal stratification data from a single fluid mechanics run at motored conditions. This is possible because thermal stratification is more sensitive to engine geometry than to operating conditions. In this article, accuracy of accelerated multizone for engine cycle simulation is demonstrated by comparison with experimental data for iso-octane homogeneous charge compression ignition operation over a broad range of lean equivalence ratios (0.14–0.28). The validated accelerated multizone for engine cycle simulation model is then applied to generating a performance map for an engine controlled by appropriately adjusting equivalence ratio and internal exhaust gas recirculation. Regions of acceptable and optimum combustion are identified. It is finally demonstrated that while indicated mean effective pressure remains low for optimum homogeneous charge compression ignition operation (1–4 bar), this is sufficient for a large fraction of typical driving in light-duty vehicles. Much driving including idle can therefore be done in homogeneous charge compression ignition mode at high efficiency and low (essentially zero) NOx and particulate matter emissions.

30 DIRECT ENERGY CONVERSION↗
NASA NTRS2009

Boundary Layer Transition Protuberance Tests at NASA JSC Arc-Jet Facility

A series of arc-jet tests in support of the Shuttle Orbiter Boundary Layer Transition flight experiment was conducted in the Channel Nozzle of the NASA Johnson Space Center Atmospheric Reentry Materials and Structures Facility. The boundary layer trip was a protrusion of a certain height and geometry fabricated as part of a 6"x6" tile insert, a special test article made of the Boeing Rigid Insulation tile material and coated with the Reaction Cured Glass used for the bottom fuselage tiles of the Space Shuttle Orbiter. A total of five such tile inserts were manufactured: four with the 0.25-in. trip height, and one with the 0.35-in. trip height. The tile inserts were interchangeably installed in the center of the 24"x24" variable configuration tile array mounted in the 24"x24" test section of the channel nozzle. The objectives of the test series were to demonstrate that the boundary layer trip can safely withstand the Space Shuttle Orbiter flight-like re-entry environments and provide temperature data on the protrusion surface, surfaces of the nearby tiles upstream and downstream of the trip, as well as the bond line between the tiles and the structure. The targeted test environments were defined for the tip of the protrusion, away from the nominal surface of the tile array. The arc jet test conditions were approximated in order to produce the levels of the free stream total enthalpy at the protrusion height similar to those expected in flight. The test articles were instrumented with surface, sidewall and bond line thermocouples. Additionally, Tempilaq temperature-indicating paint was applied to the nominal tiles of the tile array in locations not interfering with the protrusion trip. Five different grades of paint were used that disintegrate at different temperatures between 1500 and 2000 deg F. The intent of using the paint was to gauge the RCG-coated tile surface temperature, as well as determine its usefulness for a flight experiment. This paper provides an overview of the channel nozzle arc jet, test articles and test conditions, as well as the results of the arc-jet tests including the measured temperature response of the test articles, their pre- and post-test surface scans, condition of the thermal paint, and continents on the protrusion tip heating achieved in tests compared to the computational fluid dynamics predictions.

Larin, M. E.↗
NASA NTRS1994

High-lift flow-physics flight experiments on a subsonic civil transport aircraft (B737-100)

As part of the subsonic transport high-lift program, flight experiments are being conducted using NASA Langley's B737-100 to measure the flow characteristics of the multi-element high-lift system at full-scale high-Reynolds-number conditions. The instrumentation consists of hot-film anemometers to measure boundary-layer states, an infra-red camera to detect transition from laminar to turbulent flow, Preston tubes to measure wall shear stress, boundary-layer rakes to measure off-surface velocity profiles, and pressure orifices to measure surface pressure distributions. The initial phase of this research project was recently concluded with two flights on July 14. This phase consisted of a total of twenty flights over a period of about ten weeks. In the coming months the data obtained in this initial set of flight experiments will be analyzed and the results will be used to finalize the instrumentation layout for the next set of flight experiments scheduled for Winter and Spring of 1995. The main goal of these upcoming flights will be: (1) to measure more detailed surface pressure distributions across the wing for a range of flight conditions and flap settings; (2) to visualize the surface flows across the multi-element wing at high-lift conditions using fluorescent mini tufts; and (3) to measure in more detail the changes in boundary-layer state on the various flap elements as a result of changes in flight condition and flap deflection. These flight measured results are being correlated with experimental data measured in ground-based facilities as well as with computational data calculated with methods based on the Navier-Stokes equations or a reduced set of these equations. Also these results provide insight into the extent of laminar flow that exists on actual multi-element lifting surfaces at full-scale high-life conditions. Preliminary results indicate that depending on the deflection angle, the slat and flap elements have significant regions of laminar flow over a wide range of angles of attack. Boundary-layer transition mechanisms that were observed include attachment-line contamination on the slat and inflectional instability on the slat and fore flap. Also, the results agree fairly well with the predictions reported in a paper presented at last year's AIAA Fluid Dynamics Conference. The fact that extended regions of laminar flow are shown to exist on the various elements of the high-lift system raises the question what the effect is of loss of laminar flow as a result of insect contamiantion, rain or ice accumulation on high-life performance.

Vandam, Cornelis P.↗
DOE OSTI2022

Coupling Subsurface and Above-Surface Models for Optimizing the Design of Borefields and District Heating and Cooling Systems

Accurate dynamic energy simulation is important for the design and sizing of district heating and cooling systems with geothermal heat exchange for seasonal energy storage. Current modeling approaches in building and district energy simulation tools typically consider heat conduction through the ground between boreholes without flowing groundwater. While detailed simulation tools for subsurface heat and mass transfer exist, these fall short in simulating above-surface energy systems. To support the design and operation of such systems, the study developed a coupled model including a software package for building and district energy simulation, and software for detailed heat and mass transfer in the subsurface. For the first, it uses the open-source Modelica Buildings Library, which includes dynamic simulation models for building and district energy and control systems. For the heat and mass transfer in the soil, it uses the TOUGH simulator. The TOUGH family of codes can model heat and multi-phase, multi-component mass transport for a variety of fluid systems, as well as chemical reactions, in fractured porous media. The study validated the coupled modeling approach by comparing the simulation results with one from the g-function based ground response model. It then looked into effects when the water table and the regional groundwater flow are considered in the ground, from the perspective of heat exchange between borehole and ground, and the electrical consumption of the district heating and cooling systems. To access the simulation models, please find the links in the submission: -- For coupled approach validation: see model Buildings.Fluid.Geothermal.Borefields.Examples.BorefieldsWithTough and Buildings.Examples.DistrictReservoirNetworks.Examples.Reservoir3Variable_TOUGH from the "Modelica Building Library" resource, branch issue1495_tough_interface, commit a2667c0. -- For the study of the effect of water table: see model Buildings.Examples.DistrictReservoirNetworks.Examples.Reservoir3Variable_TOUGH from he "Modelica Building Library" resource, branch issue1495_tough_interface_moreIO, commit 760de49. -- For the study of the effect of regional groundwater flow: see Buildings.Examples.DistrictReservoirNetworks.Examples.Reservoir3Variable_TOUGH from he "Modelica Building Library" resource, branch issue1495_tough_interface_moreIO_3D, commit c2a2d2a. The coupling interface script "GrounResponse.py" can be found from the above links in the folder Buildings/Resources/Python-Sources. Also, the needed files for TOUGH simulation are in the folder Buildings/Resources/Python-Sources/ToughFiles that can be accessed through the above links. A brief description of these files is given below; detailed specifications for the first three files may be found in the TOUGH3 Users Guide (Jung et al., 2018) https://tough.lbl.gov/documentation/tough-manuals/. (1) INCON - initial conditions for each grid block (2) INFILE - main input file with material properties and control parameters (3) MESH - description of the computational grid (4) readsave - Modelica/TOUGH interface program: read the final output of TOUGH simulation after TOUGH time step and prepare for transfer to Modelica for next Modelica time step (5) readsave.inp - input parameters for program readsave (6) writeincon - Modelica/TOUGH interface program: write the output of Modelica after Modelica time step and prepare for transfer to TOUGH as initial conditions for the next TOUGH step (7) writeincon.inp - input parameters for program writeincon

15 GEOTHERMAL ENERGY↗
NASA NTRSDate not supplied

Computational Modeling of Mars Retropropulsion Concepts in the Langley Unitary Plan Wind Tunnel

Future human Mars missions will require powered descent starting at supersonic conditions, something which has never been done before at Mars. Computational powered descent flowfield simulations have been completed at full-scale Mars conditions, but the available ground test data are not appropriate for calibrating computational uncertainties for aerodynamic interference on proposed Mars descent vehicles. A test will be conducted in the NASA Langley Unitary Plan Wind Tunnel to begin addressing powered descent aerodynamics risks for large-scale human Mars entry concepts and to identify gaps in computational predictive capabilities. This paper covers pre-test computational flowfield predictions of two different models derived from full-scale reference vehicles: a blunt low lift-to-drag vehicle and a more slender geometry. Calculations of the blunt model include variations in nozzle configuration: nozzle location, size, area ratio, and pointing direction. There exist some significant differences between solvers, but some general trends are observed from simulations of the blunt model. First, aerodynamic axial force from the heatshield decreases with increasing thrust due to expanding plume blockage. Second, nozzles that point along the model axis result in lower aerodynamic axial force compared to nozzles that have a radial thrust component. Finally, placing the nozzles further away from the model nose preserves more heatshield axial force with increasing thrust com- pared to nozzles that are closer to the nose. For the slender model, the axial force from the heatshield is similar to the non-blowing axial force regardless of thrust magnitude, due to the nozzle arrangement on the heatshield. Once the test is completed, direct comparisons between the computations and test data will be made to determine computational uncertainties in a wind tunnel environment, to identify gaps in predictive capabilities, and to inform planning for future ground and flight test programs for Mars powered descent vehicles.

Mars↗
NASA NTRS2004

Collaborative Aerospace Research and Fellowship Program at NASA Glenn Research Center

During the summer of 2004, a 10-week activity for university faculty entitled the NASA-OAI Collaborative Aerospace Research and Fellowship Program (CFP) was conducted at the NASA Glenn Research Center in collaboration with the Ohio Aerospace Institute (OAI). This is a companion program to the highly successful NASA Faculty Fellowship Program and its predecessor, the NASA-ASEE Summer Faculty Fellowship Program that operated for 38 years at Glenn. The objectives of CFP parallel those of its companion, viz., (1) to further the professional knowledge of qualified engineering and science faculty,(2) to stimulate an exchange of ideas between teaching participants and employees of NASA, (3) to enrich and refresh the research and teaching activities of participants institutions, and (4) to contribute to the research objectives of Glenn. However, CFP, unlike the NASA program, permits faculty to be in residence for more than two summers and does not limit participation to United States citizens. Selected fellows spend 10 weeks at Glenn working on research problems in collaboration with NASA colleagues and participating in related activities of the NASA-ASEE program. This year's program began officially on June 1, 2004 and continued through August 7, 2004. Several fellows had program dates that differed from the official dates because university schedules vary and because some of the summer research projects warranted a time extension beyond the 10 weeks for satisfactory completion of the work. The stipend paid to the fellows was $1200 per week and a relocation allowance of $1000 was paid to those living outside a 50-mile radius of the Center. In post-program surveys from this and previous years, the faculty cited numerous instances where participation in the program has led to new courses, new research projects, new laboratory experiments, and grants from NASA to continue the work initiated during the summer. Many of the fellows mentioned amplifying material, both in undergraduate and graduate courses, on the basis of the summer s experience at Glenn. A number of 2004 fellows indicated that proposals to NASA will grow out of their summer research projects. In addition, some journal articles and NASA publications will result from this past summer s activities. Fellows from past summers continue to send reprints of articles that resulted from work initiated at Glenn. This report is intended primarily to summarize the research activities comprising the 2004 CFP Program at Glenn. Particular research studies include: 1) Development of an Imaging-Based, Computational Fluid Dynamics Tool to Assess Fluid Mechanics in Experimental Models that Simulate Blood Vessels; 2) Analysis of Nanomaterials Produced from Precursors; and 3) LEO Propagation Analysis Tool.

Heyward, Ann O.↗
DOE OSTI2025

Scalability analysis of heavy-duty gas turbines using data-driven machine learning

With the increasing integration of variable renewable energy sources into power systems, the role of flexible power generation technologies like gas turbines (GT) in rapid grid balancing remains crucial. This sustained importance underscores the need for scaled and precise modeling of GT to ensure effective integration within evolving energy frameworks. While physics-driven GT models integrate thermodynamics, fluid dynamics, and combustion principles, they often rely on approximate mathematical representations to accommodate scaling that may not capture the actual complex dynamics for GTs and inertial effects associated to GTs with different ratings. In this study, a data-driven model is proposed using machine learning (ML) techniques to conduct GT scalability analysis and performance evaluation with high accuracy. The ML model, trained on data from various operating conditions and performance parameters, aims to uncover intricate relationships and patterns, resembling GT characteristics at different scales (ratings). The model is developed to capture complex system interaction and to adapt to changing operational scenarios at different capacities, providing valuable insights of power system dynamics. In this study, the real-time digital simulator platform was employed to generate training data for the ML model and assess its dynamic characteristics. The ultimate objective was to develop a detailed modeling framework based on governing equations and data-driven ML capable of predicting key performance indicators, in thermal systems such as GTs, including power output, speed, fuel consumption, and exhaust temperature under diverse operating conditions at different scales. The developed ML framework demonstrated high accuracy, with mean relative errors for GT power prediction, reference speed, exhaust temperature, and compressor pressure ratio (CPR) parameters consistently below 0.1% across typical load fluctuation scenarios. Maximum deviations were limited to approximately 0.5 K for exhaust temperature and 0.009 for CPR, underscoring the model’s ability to replicating dynamic GT behavior with high precision. The adaptability of the ML model enables its application across diverse operational conditions and its extension to other thermal systems. By leveraging advanced ML techniques, this study presents a robust and scalable modeling framework that enhances GT simulation precision, facilitating improved integration into evolving power systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

An intercomparison of wall fluxes in a turbulent thermal convection chamber: Direct numerical simulations and wall-modeled large-eddy simulations enhanced by machine learning

Thermal convection in a closed chamber is driven by a warm bottom, a cold top, and side walls at various temperatures. Although wall fluxes are the source of convection energy, accurately modeling these fluxes (i.e., the wall model) is challenging. In large-eddy simulations (LESs), many wall models are traditionally derived from the canonical boundary layer, which may be unsuitable for thermal convection bounded by both horizontal and vertical walls. This study conducts a model intercomparison of dry convection in a cubic-meter chamber using three direct numerical simulations (DNSs) and four LESs with different wall models. The LESs employ traditional wall models, a new wall model employing physics-aware neural networks, and a refined grid near the walls. The experiment involves four cases with varying sidewall temperatures. Our results show that LESs capture the main flow features and the trends of mean fluxes. The physics-aware neural networks and refined wall grids can improve the temporally averaged local fluxes when the large-scale circulation has a preferred direction. Even without the local improvement of wall fluxes, the LES flow quantities (temperature and velocities) can still largely match those in DNSs, provided the mean flux largely matches the DNSs. Additionally, DNSs reveal that a variation in corner treatments has minimal impacts on the flow quantities away from corners. Finally, LESs underestimate the mean fluxes of the entire wall due to their inability to resolve corner regions, but their mean flux away from the corner can better match DNS.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Two-dimensional mapping of absolute OH densities in an atmospheric pressure plasma effluent via planar laser-induced fluorescence: effects of He/H 2 O and He/O 2 mixtures in N 2 and air, with and without solid targets

Planar laser-induced fluorescence (LIF) was employed to measure the absolute density of hydroxyl radicals (OH) in the effluent of the COST Reference Microplasma Jet for two feed gas mixtures: He/H 2 O and He/O 2 . Experiments were conducted with the effluent propagating into air and N 2 environments. For the He/H 2 O case, measurements were also performed with the effluent impinging on a solid target at varying distances from the jet nozzle. Calibration of the OH-LIF signal from the COST-Jet was achieved by comparing it to a reference signal generated by the photofragmentation of H 2 O 2 . Results demonstrated that OH densities were sustained longer when the effluent propagates in a nitrogen environment compared to air, particularly with water added to the feed gas. The broader OH distribution in N 2 suggests slower consumption due to the absence of oxygen, which accelerates OH depletion in air via reactions involving O 2 and HO 2 . Even when water was not added to the feed, as in the He/O 2 case, appreciable OH densities were observed, due to gas impurities and reactive species interactions with atmospheric humidity, forming reaction fronts that delineate the gas flow. Two-dimensional fluid dynamics simulations elucidated the influence of atmospheric gas entrainment and solid targets on the OH distribution. Experimental trends were further compared with a zero-dimensional chemistry model to explore OH production and consumption mechanisms in air and nitrogen environments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗