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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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All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Unsteady Pressure Measurements on a Simplified High-Lift Configuration of the Common Research Model using Active Flow Control

The High-Lift Common Research Model (CRM-HL) is a product of the NASA Advanced Air Transport Technology (AATT) Project intended to study various high-lift aerodynamic phenomena including enhanced lift, acoustic noise generation, and optimum placement of leading and trailing-edge devices. The current study was conducted in the NASA Langley 14-by 22-Foot Subsonic Tunnel (14x22) for the purpose of evaluating enhanced lift through the use of active flow control (AFC). The current paper documents the effect of sweeping-jet actuation combined with steady blowing on a simplified high-lift configuration using unsteady pressure measurements. The time-series parameters for the measurements are documented as well as the data acquisition system used to acquire the data. An uncertainty analysis will be presented in order to document the system performance and provide an estimate of the data quality. Repeatability of the data will be shown along with trends associated with model angle of attack, and also those associated with changes in the nozzle pressure ratio (NPR) of the AFC system.

Active Flow Control↗
DOE OSTI2025

The impact of capillary heterogeneity on CO 2 flow and trapping across scales

Capillary heterogeneity has been identified over the last decade as a key control on subsurface CO 2 flow behavior during geological CO 2 sequestration. These heterogeneities can be formed in all sedimentary rocks, ranging from slight variations in the sand grain sizes to extensive sequences of interbedded sands, shales, and limestones. Capillary heterogeneity has been largely, although not entirely, overlooked in subsurface flow modeling because it is assumed to only directly influence fluid redistribution over scales of centimeters to meters. However, even small-scale fluid movements can result in dramatic impacts on the mobility and trapping of the CO 2 over kilometers. Therefore, neglecting capillary heterogeneity at multiple scales could potentially lead to errors in modeling and predicting field-scale plume migration. In this review paper, we aim to provide a consistent overview to (1) establish that capillary heterogeneity can have a major impact on CO 2 plume migration, (2) establish the respective length scales at which capillary heterogeneity matters, and (3) provide guidance for numerical modeling. This review covers pertinent literature and extracts key observations from the core to the field scales. Experimental studies have shown that millimeter-decimeter scale capillary heterogeneity can cause the so-called capillary heterogeneity trapping in addition to pore-scale residual trapping. Even at such a small scale, capillary heterogeneity can already lead to complex upscaled constitutive relationships, such as flow-rate dependent and anisotropic relative permeability, which affects field-scale CO 2 migration even when field-scale heterogeneities are present. Under gravity-dominated flow regimes, centimeter-meter scale capillary heterogeneity can entrap a significant amount of CO 2 at field scale, not just after imbibition but also during drainage. In certain cases, the presence of capillary heterogeneity can even completely stop the vertical movement of the CO 2 plume, hence greatly reducing leakage risks. At meter-kilometer scale, the influence of capillary heterogeneity is more pronounced and can hinder or redirect CO 2 migration in both lateral and vertical directions. The impact of capillary heterogeneity across multiple spatial scales poses a great challenge in modeling CO 2 migration at field scale, because it is practically impossible to build a field-scale earth model with grid blocks at millimeter scale. We recommend a hierarchical modeling approach to address this challenge. At field scale, earth models are built to capture geological features and heterogeneities in high but still practical grid resolutions. For each facies or rock type of the field-scale model, high- resolution meter-scale “conceptual” models are built with millimeter-scale grid blocks to capture representative fine-scale bedding geometries and heterogeneities in various environments of deposition, bridging the gap from subcore scale to the size of a field-scale simulation grid block. Upscaling is then used to preserve the smaller-scale flow dynamics of various rock types in field-scale simulations. Here, future work is needed to (1) refine, improve, and validate the hierarchical modeling approach; (2) build libraries of fine-scale bedding models for facies in various environments of deposition; (3) quantify multiscale capillary heterogeneity effects under subsurface uncertainties; (4) gain learning from different storage formations; and (5) establish best practices that balance accuracy and computational speed.

Capillary heterogeneity↗
NASA NTRS2013

Experimental Investigation of Shock-Shock Interactions Over a 2-D Wedge at M=6

The effects of fin-leading-edge radius and sweep angle on peak heating rates due to shock-shock interactions were investigated in the NASA Langley Research Center 20-inch Mach 6 Air Tunnel. The fin model leading edges, which represent cylindrical leading edges or struts on hypersonic vehicles, were varied from 0.25 inches to 0.75 inches in radius. A 9deg wedge generated a planar oblique shock at 16.7deg to the flow that intersected the fin bow shock, producing a shock-shock interaction that impinged on the fin leading edge. The fin angle of attack was varied from 0deg (normal to the free-stream) to 15deg and 25deg swept forward. Global temperature data was obtained from the surface of the fused silica fins through phosphor thermography. Metal oil flow models with the same geometries as the fused silica models were used to visualize the streamline patterns for each angle of attack. High-speed zoom-schlieren videos were recorded to show the features and temporal unsteadiness of the shock-shock interactions. The temperature data were analyzed using one-dimensional semi-infinite as well as one- and two-dimensional finite-volume methods to determine the proper heat transfer analysis approach to minimize errors from lateral heat conduction due to the presence of strong surface temperature gradients induced by the shock interactions. The general trends in the leading-edge heat transfer behavior were similar for the three shock-shock interactions, respectively, between the test articles with varying leading-edge radius. The dimensional peak heat transfer coefficient augmentation increased with decreasing leading-edge radius. The dimensional peak heat transfer output from the two-dimensional code was about 20% higher than the value from a standard, semi-infinite one-dimensional method.

Jones, Michelle L.↗
NASA NTRS2013

Thermographic Phosphor Measurements of Shock-Shock Interactions on a Swept Cylinder

The effects of fin leading-edge radius and sweep angle on peak heating rates due to shock-shock interactions were investigated in the NASA Langley Research Center 20-inch Mach 6 Air Tunnel. The fin model leading edges, which represent cylindrical leading edges or struts on hypersonic vehicles, were varied from 0.25 inches to 0.75 inches in radius. A 9deg wedge generated a planar oblique shock at 16.7deg to the flow that intersected the fin bow shock, producing a shock-shock interaction that impinged on the fin leading edge. The fin angle of attack was varied from 0deg (normal to the free-stream) to 15deg and 25deg swept forward. Global temperature data was obtained from the surface of the fused silica fins using phosphor thermography. Metal oil flow models with the same geometries as the fused silica models were used to visualize the streamline patterns for each angle of attack. High-speed zoom-schlieren videos were recorded to show the features and temporal unsteadiness of the shock-shock interactions. The temperature data were analyzed using one-dimensional semi-infinite as well as one- and two-dimensional finite-volume methods to determine the proper heat transfer analysis approach to minimize errors from lateral heat conduction due to the presence of strong surface temperature gradients induced by the shock interactions. The general trends in the leading-edge heat transfer behavior were similar for the three shock-shock interactions, respectively, between the test articles with varying leading-edge radius. The dimensional peak heat transfer coefficient augmentation increased with decreasing leading-edge radius. The dimensional peak heat transfer output from the two-dimensional code was about 20% higher than the value from a standard, semi-infinite onedimensional method.

Jones, Michelle L.↗
DOE OSTI2022

Toward a machine-guided approach to energetic material discovery

In this article, we trained a machine learning (ML) model to connect microstructural details of an energetic material formulation to its performance for the purpose of guiding the discovery of new explosive formulations. Our hypothesis was that the algorithm would robustly learn the training data and produce an accurate surrogate model. Specifically, the algorithm learned the relationship between details of the void size distribution (VSD), initiating shock pressure, and the energetic material performance. We used realistic constraints on the VSD and a range of cases were ingested by a physically informed reactive flow model working within a hydrodynamic solver running on high-performance computing resources. The ML algorithm produced a surrogate model that accurately predicted known test points around the parameter space. In addition to the utility of the model and the process used for its development, we noted interesting comparisons between what we, the authors—subject matter experts, would heuristically conclude from the training data and the surrogate model predictions. We detected nuanced details that were missed by the surrogate model; however, these details are not important to an energetic material formulator. We concluded that the algorithm did indeed robustly learn the training data and produce an accurate surrogate model. We further concluded that the surrogate model is a powerful tool to guide the formulator in the absence of subject matter experts and limited-access computing resources.

42 ENGINEERING↗
DOE OSTI2024

Modeling Radionuclide Inventories in MSR Off-Gas Systems with Radiochemical Transport Analysis

Molten salt reactors (MSR) contain unique characteristics that may require enhancements to modeling tools to accurately predict phenomena. One characteristic that may be advantageous to leverage during normal operation is on-line processing of the circulating fuel salt, such as an off-gas system (OGS) to remove volatile fission products. Therefore, new modeling tools must be developed to integrate spatial resolution and chemistry effects into fuel depletion tools to be able to account for these non-core sources of radioactivity. Such types of radiochemical transport analysis tools were used to estimate the removal rates for 12 elements within a flow model of the Molten Salt Reactor Experiment (MSRE) by optimizing against legacy experimental data of the gas-borne (GB) percentages of 12 nuclides. The removal rates were used in a depletion model to calculate the FP inventory that enters the MSRE OGS. Calculations are in good agreement with the empirical GB percentages reported for the 12 nuclides, which validates the approach and verifies each tool’s treatment of the radiochemical flow effects. The OGS inventory is discussed in terms of the largest nuclide contributors to activity, dose consequence, decay heat, and elemental composition. Finally, insights from the study allow recommendations to be made for future code development activities.

Shahbazi, Shayan↗
DOE OSTI2024

a priori uncertainty quantification of reacting turbulence closure models using Bayesian neural networks

While many physics-based closure model forms have been posited for the sub-filter scale (SFS) in large eddy simulation (LES), vast amounts of data available from direct numerical simulations (DNS) create opportunities to leverage data-driven modeling techniques. Albeit flexible, data-driven models still depend on the dataset and the functional form of the model chosen. Increased adoption of such models requires reliable uncertainty estimates both in the data-informed and out-of-distribution regimes. Here, in this work, we employ Bayesian neural networks (BNNs) to capture both epistemic and aleatoric uncertainties in a reacting flow model. In particular, we model the filtered progress variable scalar dissipation rate which plays a key role in the dynamics of turbulent premixed flames. We demonstrate that BNN models can provide unique insights about the structure of uncertainty of the data-driven closure models. We also propose a method for the incorporation of out-of-distribution information in a BNN, which can be used for out-of-distribution query detection. The efficacy of the model is demonstrated by a priori evaluation on a dataset consisting of a variety of flame conditions and fuels.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1996

On modeling pressure diffusion in non-homogeneous shear flows

New models are proposed for the 'slow and 'rapid' parts of the pressure diffusive transport based on the examination of DNS databases for plane mixing layers and wakes. The model for the 'slow' part is non-local, but requires the distribution of the triple-velocity correlation as a local source. The latter can be computed accurately for the normal component from standard gradient diffusion models, but such models are inadequate for the cross component. More work is required to remedy this situation.

Demuren, A. O.↗
DOE OSTI2022

Process Interactions Can Change Process Ranking in a Coupled Complex System Under Process Model and Parametric Uncertainty

For a complex hydrologic system with multiple processes and process interactions, global sensitivity analysis is often used to identify important or influential parameters for model development and improvement. The identification is complicated by process model uncertainty, when a system process can be represented by multiple process models. This study develops a new total-effect process sensitivity index to identify influential processes under model uncertainty. This is done by extending Sobol's total-effect parameter sensitivity index for one system model to total-effect process sensitivity index for multiple system models to account for uncertainty in process models and model parameters. The total-effect process sensitivity index includes not only the first-order process sensitivity index for measuring the importance of individual processes but also higher-order indices that account for process interactions. The total-effect process sensitivity index can identify an influential process that itself and its interactions with other processes influence a model output. Here, the total-effect process sensitivity index is applied to two numerical examples: (a) Sobol's G*-functions with analytical solutions of first-order and total-effect process sensitivity indices, and (b) groundwater flow models with interactions between recharge, geology, and snowmelt processes. The second evaluation shows that, due to second-order and higher-order process interactions, the first-order and total-effect process sensitivity indices give different process ranking. It is thus necessary to estimate both first-order and total-effect process sensitivity indices to appreciate the difference between the first-order impact of a process alone and the overall total-effect impact of the process itself and its interactions with other processes on a model output.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2016

Wind Tunnel Interference Effects on Tilt Rotor Testing Using Computational Fluid Dynamics

Experimental techniques to measure rotorcraft aerodynamic performance are widely used. However, most of them are either unable to capture interference effects from bodies, or require an extremely large computational budget. The objective of the present research is to develop an XV-15 Tiltrotor Research Aircraft rotor model for investigation of wind tunnel wall interference using a novel Computational Fluid Dynamics (CFD) solver for rotorcraft, RotCFD. In RotCFD, a mid-fidelity Unsteady Reynolds Averaged Navier-Stokes (URANS) solver is used with an incompressible flow model and a realizable k-ε turbulence model. The rotor is, however, not modeled using a computationally expensive, unsteady viscous body-fitted grid, but is instead modeled using a blade-element model (BEM) with a momentum source approach. Various flight modes of the XV-15 isolated rotor, including hover, tilt, and airplane mode, have been simulated and correlated to existing experimental and theoretical data. The rotor model is subsequently used for wind tunnel wall interference simulations in the National Full-Scale Aerodynamics Complex (NFAC) at Ames Research Center in California. The results from the validation of the isolated rotor performance showed good correlation with experimental and theoretical data. The results were on par with known theoretical analyses. In RotCFD the setup, grid generation, and running of cases is faster than many CFD codes, which makes it a useful engineering tool. Performance predictions need not be as accurate as high-fidelity CFD codes, as long as wall effects can be properly simulated. For both test sections of the NFAC wall, interference was examined by simulating the XV-15 rotor in the test section of the wind tunnel and with an identical grid but extended boundaries in free field. Both cases were also examined with an isolated rotor or with the rotor mounted on the modeled geometry of the Tiltrotor Test Rig (TTR). A "quasi linear trim" was used to trim the thrust for the rotor to compare the power as a unique variable. Power differences between free field and wind tunnel cases were found from -7 to 0 percent in the 80- by 120-Foot Wind Tunnel and -1.6 to 4.8 percent in the 40- by 80-Foot Wind Tunnel, depending on the TTR orientation, tunnel velocity, and blade setting. The TTR will be used in 2016 to test the Bell 609 rotor in a similar fashion to the research in this report.

CFD↗
NASA NTRS1984

Tunnel constraint for a jet in crossflow

A facet of a unified tunnel correction scheme which uses wall pressures to determine tunnel induced blockage and upwash is described. With this method, there is usually no need to use data concerning model forces or power settings to find the interference; it follows directly from the pressures and tunnel dimensions. However, highly inclined jets do not produce good pressure signatures and are highly three dimensional, so they must be treated differently. Flow modeling is also discussed.

Wilsden, D. J.↗
NASA NTRS1990

Advanced air revitalization system modeling and testing

To support manned lunar and Martian exploration, an extensive evaluation of air revitalization subsystems (ARS) is being conducted. The major operations under study include carbon dioxide removal and reduction; oxygen and nitrogen production, storage, and distribution; humidity and temperature control; and trace contaminant control. A comprehensive analysis program based on a generalized block flow model was developed to facilitate the evaluation of various processes and their interaction. ASPEN PLUS was used in modelling carbon dioxide removal and reduction. Several life support test stands were developed to test new and existing technologies for their potential applicability in space. The goal was to identify processes which use compact, lightweight equipment and maximize the recovery of oxygen and water. The carbon dioxide removal test stands include solid amine/vacuum desorption (SAVD), regenerative silver oxide chemisorption, and electrochemical carbon dioxide concentration (EDC). Membrane-based carbon dioxide removal and humidity control, catalytic reduction of carbon dioxide, and catalytic oxidation of trace contaminants were also investigated.

Dall-Baumann, Liese↗
NASA NTRS2023

Python Based Plume Dynamics Estimation Tool (PyPDET) Rapid Plume Strike Analysis for RPOD Maneuvers in Deep Space Operations

I worked as a NASA Intern during the Summer 2023 term in the DS-00 division under the supervision of my mentor, Dr. Jonathan Pitt. Our goal was to build on our previous work from 2022 to develop a plume strike estimation tool using a prescribed physics methodology and model plume impingement effects while considering the dynamics of a rendezvous, operations, proximity, and docking (RPOD) maneuver. This tool supports previously configured CFD-DSMC calculations by allowing for rapid analysis of initial designs using a low-fidelity source flow model. Engineers can then use the high-fidelity CFD-DSMC tool to consolidate results as they work towards finalizing a design. This year’s project was focused on developing a software application that other engineers would be using in their analysis. Thus, the user’s experience was considered in the development of this application. Proper documentation, testability, and modularity of the codebase was our priority. For example, the project included auto documentation procedures to start building towards a User Manual, while also including dedicated demonstration cases for more explicit communication of functionality. Also, this project included a framework for testing the source code for future developments. Additionally, care was taken to develop the code using an Object-Oriented Programming approach. Thus, allowing for a modular extensibility of functionality in anticipation of future developments. The core work of this project was developing an algorithm that would transform the visiting vehicle and associated thruster data according to the kinematics described in the jet firing history. It would then calculate the estimated plume strikes on two of the target vehicles and write data accordingly into a VTK file. Summer work is to conclude by developing and presenting a PowerPoint slide deck at the intern exit briefing on August 11 th , 2023. Once the model for simple plume strike calculations is developed and tested there are several avenues to explore to continue development of this tool. These are also discussed in this report.

Plume Impingement↗
DOE OSTI2025

Can Large Language Models Understand Intermediate Representations?

Intermediate Representations (IRs) are essential in compiler design and program analysis, yet their comprehension by Large Language Models (LLMs) remains underexplored. This paper presents a pioneering empirical study to investigate the capabilities of LLMs, including GPT-4, GPT-3, Gemma 2, LLaMA 3.1, and Code Llama, in understanding IRs. We analyze their performance across four tasks: Control Flow Graph (CFG) reconstruction, decompilation, code summarization, and execution reasoning. Our results indicate that while LLMs demonstrate competence in parsing IR syntax and recognizing high-level structures, they struggle with control flow reasoning, execution semantics, and loop handling. Specifically, they often misinterpret branching instructions, omit critical IR operations, and rely on heuristic-based reasoning, leading to errors in CFG reconstruction, IR decompilation, and execution reasoning. The study underscores the necessity for IR-specific enhancements in LLMs, recommending fine-tuning on structured IR datasets and integration of explicit control flow models to augment their comprehension and handling of IR-related tasks.

Jiang, Hailong↗
DOE OSTI2026

Hydrogen Production Cost from Proton-Conducting Solid Oxide Electrolysis

Rigorous stakeholder-vetted techno-economic analysis (TEA) was conducted to estimate the cost of hydrogen (H 2 ) production using Proton-Conducting Solid Oxide (PSO) electrolysis. The analysis evaluates Current (2025) and Future (2035) technology cases at centralized plant scales of 50 and 500 metric tonnes per day (MTD), assuming electricity, water, and air as the only system inputs. Untaxed, unsubsidized levelized cost of hydrogen (LCOH) is projected to range from 2020 $\$$1.81 to $\$$2.47/kg H 2 at an electricity price of $\$$0.03/kWh and 97% capacity factor under Nth-of-a-kind (NOAK) deployment assumptions. Total installed capital cost was developed using bottom-up Design for Manufacture and Assembly (DFMA) stack cost modeling and detailed balance-of-plant estimates, including mechanical and electrical subsystems, installation, site preparation, engineering, and contingency. Stack performance assumptions include thermoneutral operation, degradation over time, and periodic replacement. LCOH was calculated using the Hydrogen Analysis (H2A) discounted cash flow model in constant 2020 dollars. Results indicate PSO electrolysis has potential for competitive hydrogen production costs under low-cost electricity and mature manufacturing conditions.

08 HYDROGEN↗
NASA NTRS1992

What we learn about cooling flows through the study of the 10,000 K gas in clusters

The physical properties of the emission-line nebulae associated with central dominant galaxies in clusters are explored within the context of standard cooling-flow models of the hot ICM. It is pointed out that the properties of the 10,000 K gas are inconsistent with simple theories in which this gas has accreted out of the hot ICM in thermal instabilities within a standard cooling flow atmosphere. Several possible ramifications for our understanding of the properties of clusters and the hot intracluster medium are discussed.

Baum, Stefi A.↗