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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Unified many-worlds browsing of arbitrary physics-based animations

Manually tuning physics-based animation parameters to explore a simulation outcome space or achieve desired motion outcomes can be notoriously tedious. This problem has motivated many sophisticated and specialized optimization-based methods for fine-grained (keyframe) control, each of which are typically limited to specific animation phenomena, usually complicated, and, unfortunately, not widely used. In this paper, we propose Unified Many-Worlds Browsing (UMWB), a practical method for sample-level control and exploration of physics-based animations. Our approach supports browsing of large simulation ensembles of arbitrary animation phenomena by using a unified volumetric WORLDPACK representation based on spatiotemporally compressed voxel data associated with geometric occupancy and other low-fidelity animation state. Beyond memory reduction, the WORLDPACK representation also enables unified query support for interactive browsing: it provides fast evaluation of approximate spatiotemporal queries, such as occupancy tests that find ensemble samples ("worlds") where material is either IN or NOT IN a user-specified spacetime region. WORLDPACKS also support real-time hardware-accelerated voxel rendering by exploiting the spatially hierarchical and temporal RLE raster data structure. Our UMWB implementation supports interactive browsing (and offline refinement) of ensembles containing thousands of simulation samples, and fast spatiotemporal queries and ranking. We show UMWB results using a wide variety of physics-based animation phenomena---not just JELL-O ® .

Computer Science↗
NASA NTRSDate not supplied

Scale resolving simulations of the NASA Juncture Flow Model using the LAVA solver

Two distinct simulation methodologies: Delayed Detached Eddy Simulation (DDES) and stress based Wall-modelled Large Eddy Simulation (WMLES) are evaluated using structured overset curvilinear grids for the NASA juncture flow model. While both methodologies are shown to mitigate the primary shortcomings of steady state Reynolds Averaged Navier Stokes(RANS) simulations, several unresolved aspects are identified. Strong sensitivity to RANS-typegrid refinement is observed in the DDES with a substantial deterioration of the solution quality with increasing spatial resolution associated with deficiencies in the shielding function. Mean profiles for attached boundary layers on the fuselage show spurious inflections suggesting modelled stress depletion on finer grids. Lower numerical dissipation in terms of spatial discretization and time step size is seen to improve the solution quality, and the advantage of using RC and QCR2000 corrections in the underlying RANS closure is demonstrated for DDES on RANS-type meshes. Equilibrium Wall-Modelled LES used grids that resolved the tripping dots over the fuselage nose and the wing leading edge, consistent with the experiment setup. These simulations resulted in a cost-competitive approach compared to DDES on RANS-type grids. Although the agreement between WMLES predictions of first and second order single point statistics with experimental measurements is promising, a fundamental shortcoming is noted in terms of an overshoot in streamwise momentum in corner regions of the wing-fuselage juncture. This excess momentum subsequently delays the onset of separation,thereby resulting in an underprediction in length of the separation bubble. Some quantitative sensitivity to numerical discretization is observed; lowering of numerical dissipation shows better agreement with the experiment.

T^3↗
NASA NTRS2012

Best Merge Region Growing Segmentation with Integrated Non-Adjacent Region Object Aggregation

Best merge region growing normally produces segmentations with closed connected region objects. Recognizing that spectrally similar objects often appear in spatially separate locations, we present an approach for tightly integrating best merge region growing with non-adjacent region object aggregation, which we call Hierarchical Segmentation or HSeg. However, the original implementation of non-adjacent region object aggregation in HSeg required excessive computing time even for moderately sized images because of the required intercomparison of each region with all other regions. This problem was previously addressed by a recursive approximation of HSeg, called RHSeg. In this paper we introduce a refined implementation of non-adjacent region object aggregation in HSeg that reduces the computational requirements of HSeg without resorting to the recursive approximation. In this refinement, HSeg s region inter-comparisons among non-adjacent regions are limited to regions of a dynamically determined minimum size. We show that this refined version of HSeg can process moderately sized images in about the same amount of time as RHSeg incorporating the original HSeg. Nonetheless, RHSeg is still required for processing very large images due to its lower computer memory requirements and amenability to parallel processing. We then note a limitation of RHSeg with the original HSeg for high spatial resolution images, and show how incorporating the refined HSeg into RHSeg overcomes this limitation. The quality of the image segmentations produced by the refined HSeg is then compared with other available best merge segmentation approaches. Finally, we comment on the unique nature of the hierarchical segmentations produced by HSeg.

Tilton, James C.↗
DOE OSTI2022

Massively parallel, computationally guided design of a proenzyme

Proteins have shown promise as therapeutics and diagnostics, but their effectiveness is limited by our inability to spatially target their activity. To overcome this limitation, we developed a computationally guided method to design inactive proenzymes or zymogens, which are activated through cleavage by a protease. Since proteases are differentially expressed in various tissues and disease states, including cancer, these proenzymes could be targeted to the desired microenvironment. We tested our method on the therapeutically relevant protein carboxypeptidase G2 (CPG2). We designed Pro-CPG2s that are inhibited by 80 to 98% and are partially to fully reactivatable following protease treatment. The developed methodology, with further refinements, could pave the way for routinely designing protease-activated protein-based therapeutics and diagnostics that act in a spatially controlled manner. Confining the activity of a designed protein to a specific microenvironment would have broad-ranging applications, such as enabling cell type-specific therapeutic action by enzymes while avoiding off-target effects. While many natural enzymes are synthesized as inactive zymogens that can be activated by proteolysis, it has been challenging to redesign any chosen enzyme to be similarly stimulus responsive. Here, we develop a massively parallel computational design, screening, and next-generation sequencing-based approach for proenzyme design. For a model system, we employ carboxypeptidase G2 (CPG2), a clinically approved enzyme that has applications in both the treatment of cancer and controlling drug toxicity. Detailed kinetic characterization of the most effectively designed variants shows that they are inhibited by ∼80% compared to the unmodified protein, and their activity is fully restored following incubation with site-specific proteases. Introducing disulfide bonds between the pro- and catalytic domains based on the design models increases the degree of inhibition to 98% but decreases the degree of restoration of activity by proteolysis. A selected disulfide-containing proenzyme exhibits significantly lower activity relative to the fully activated enzyme when evaluated in cell culture. Structural and thermodynamic characterization provides detailed insights into the prodomain binding and inhibition mechanisms. The described methodology is general and could enable the design of a variety of proproteins with precise spatial regulation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

A cell-centered AMR-ALE framework for 3D multi-material hydrodynamics. Part II: linesweep ALE rezoning for nonconformal block-structured AMR meshes

The simulation of flows presenting contact discontinuities, vorticity, and large variations in spatial scales can be performed in a framework coupling Arbitrary Lagrangian Eulerian (ALE) algorithms and Adaptive Mesh Refinement (AMR). This coupling requires adaptation of ALE rezoning techniques to meshes containing nonconformal nodes arising from both the AMR topology and the junction of mesh blocks. Here, in this paper, we present an ALE rezoning strategy that is compatible with such meshes, and that can also act as a disentangling algorithm. Emphasis is put on an algorithm that respects intrinsic Lagrangian mesh properties in order to preserve accuracy around discontinuities. To that end, we adapt the weighted linesweep algorithm to nonconformal block-structured AMR meshes. Then, we present control parameters introduced in the method for it to be applicable in practical situations. Notably, the method is coupled to a specific metric optimization in order to palliate some shortcomings of the linesweep method. Finally, numerical test cases are presented that feature the capabilities of the ALE-AMR algorithm for flows that present discontinuities, vorticity, and a variety of scales. Notably, we show that our ALE-AMR algorithm gives results at least similar to Euler-AMR, but provides better accuracy in cases where discontinuities are involved, thanks to a method that respects the Lagrangian features of the mesh. Additionally, it enables Euler-AMR-like computations on domains with temporally varying domain boundaries.

Adaptive mesh refinement↗
NASA NTRS1984

An Overview of LANDSAT-4 and the Thematic Mapper

The LANDSAT 4 satellite and its orbit, the Thematic Mapper (TM) sensor design, and the ground processing of TM data are discussed. The design of LANDSAT 4 incorporates several technological advancements which include the TM. The TM offers refinements over the familiar Multispectral Scanners (MSS's) aboard all of the LANDSAT satellites in terms of spatial, spectral, and radiometric resolutions. The TM data undergo radiometric and geometric corrections on the ground to provide investigators with pictorial and digital image data products.

Irons, J. R.↗
NASA NTRS1989

Report from ionospheric science

The general strategy to advance knowledge of the ionospheric component of the solar terrestrial system should consist of a three pronged attack on the problem. Ionospheric models should be refined by utilization of existing and new data bases. The data generated in the future should emphasize spatial and temporal gradients and their relation to other events in the solar terrestrial system. In parallel with the improvement in modeling, it will be necessary to initiate a program of advanced instrument development. In particular, emphasis should be placed on the area of improved imaging techniques. The third general activity to be supported should be active experiments related to a better understanding of the basic physics of interactions occurring in the ionospheric environment. These strategies are briefly discussed.

Raitt, W. J.↗
NASA NTRS2004

Assessing Jet-Induced Spatial Mixing in a Rich, Reacting Crossflow

In many advanced low NOx gas turbine combustion techniques, such as rich-burn/quick-mix/lean-burn (RQL), jet mixing in a reacting, hot, fuel-rich crossflow plays an important role in minimizing all pollutant emissions and maximizing combustion efficiency. Assessing the degree of mixing and predicting jet penetration is critical to the optimization of the jet injection design strategy. Different passive scalar quantities, including carbon, oxygen, and helium are compared to quantify mixing in an atmospheric RQL combustion rig under reacting conditions. The results show that the O2-based jet mixture fraction underpredicts the C-based mixture fraction due to jet dilution and combustion, whereas the He tracer overpredicts it possibly due to differences in density and diffusivity. The He-method also exhibits significant scatter in the mixture fraction data that can most likely be attributed to differences in gas density and turbulent diffusivity. The jet mixture fraction data were used to evaluate planar spatial unmixedness, which showed good agreement for all three scalars. This investigation suggests that, with further technique refinement, O2 or a He tracer could be used instead of C to determine the extent of reaction and mixing in an RQL combustor.

Demayo, T. N.↗
DOE OSTI2026

High-Resolution South American Wind Resource Data Downscaled with Generative Machine Learning Conditioned on Near-Surface Observations

High-resolution historical wind data was developed for the entirety of South America using the innovative Super-Resolution for Renewable Resource Data (sup3r) machine learning framework. The publicly available Sup3rWind South America dataset represents a significant advancement in wind resource data generation, leveraging generative machine learning conditioned on near-surface observations from the Meteorological Assimilation Data Ingest System (MADIS) to efficiently and accurately downscale coarse reanalysis data from the European Centre for Medium-Range Weather Forecasts (ERA5). This approach produces fine-scale, spatially and temporally coherent wind and meteorological fields hundreds of times more computationally efficient than traditional numerical weather modeling methods, enabling access to high-fidelity wind information across both continental and offshore regions. Sup3rWind South America builds on the earlier Sup3rWind Ukraine dataset through improvements in model architecture and outputs conditioned on near-surface observation inputs. As with the Ukraine data release, this dataset includes wind speed, wind direction, temperature, relative humidity, and pressure at a horizontal resolution of ~2 km, representing a 15x spatial enhancement relative to the 31 km ERA5 grid. Wind speed and direction are provided at 5-minute resolution, a 12x temporal refinement compared to the hourly ERA5 data, while temperature, relative humidity, and pressure remain at hourly resolution. The data covers all years from 2005 to 2024. Before downscaling, ERA5 inputs were bias-corrected using long-term monthly means and a limited number of quality-controlled observations to align large-scale statistics with regional conditions. The resulting dataset is the first publicly available high-resolution timeseries wind record that provides full spatial coverage of South America. Model validation demonstrates strong agreement with observations across several statistical metrics, consistent with other state-of-the-art high-resolution wind resource datasets. The potential applications of Sup3rWind South America span renewable energy resource assessment, energy system modeling, and grid resilience analysis. The 20-year record and high spatial and temporal resolution support accurate estimation of long-term energy yield and the economic feasibility of potential wind development sites. Continuous coverage across both continental and offshore regions enables comprehensive site prospecting within exclusive economic zones. The 2 km, 5-minute resolution data provide the spatial and temporal variability required for power system simulation, operational planning, and regional risk assessments.

17 WIND ENERGY↗
DOE OSTI2024

Assessing the sensitivity of aerosol mass budget and effective radiative forcing to horizontal grid spacing in E3SMv1 using a regional refinement approach

Abstract. Atmospheric aerosols have important impacts on air quality and the Earth–atmospheric energy balance. However, as computing power is limited, Earth system models generally use coarse spatial grids and parameterize finer-scale atmospheric processes. These parameterizations and the simulation of atmospheric aerosols are often sensitive to model horizontal resolutions. Understanding the sensitivities is necessary for the development of Earth system models at higher resolutions with the deployment of more powerful supercomputers. Using the Energy Exascale Earth System Model (E3SM) version 1, this study investigates the impact of horizontal grid spacing on the simulated aerosol mass budget, aerosol–cloud interactions, and the effective radiative forcing of anthropogenic aerosols (ERFaer) over the contiguous United States. We examine the resolution sensitivity by comparing the nudged simulation results for 2016 from the low-resolution model (LR) and the regional refinement model (RRM). As expected, the simulated emissions of natural dust, sea salt, and marine organic matter are substantially higher in the RRM than in the LR. In addition, RRM simulates stronger aqueous-phase production of sulfate through the enhanced oxidation of sulfur dioxide by hydrogen peroxide due to increased cloud liquid water content. In contrast, the gas-phase chemical production of sulfate is slightly suppressed. The RRM resolves more large-scale precipitation and produces less convective precipitation than the LR, leading to increased (decreased) aerosol wet scavenging by large-scale (convective) precipitation. Regarding aerosol effects on clouds, RRM produces larger temporal variabilities in the large-scale liquid cloud fractions than LR, resulting in increased microphysical cloud processing of aerosols (more interstitial aerosols are converted to cloud-borne aerosols via aerosol activation) in RRM. Water vapor condensation is also enhanced in RRM compared to LR. Consequently, the RRM simulation produces more cloud droplets, a larger cloud droplet radius, a higher liquid water path, and a larger cloud optical depth than the LR simulation. A comparison of the present-day and pre-industrial simulations indicates that, for this contiguous United States domain, the higher-resolution increases ERFaer at the top of the model by about 12 %, which is mainly attributed to the strengthened indirect effect associated with aerosol–cloud interactions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Mapping structural heterogeneity at the nanoscale with scanning nano-structure electron microscopy (SNEM)

Here, in this work, we explore the use of scanning electron diffraction (also known as 4D-STEM) coupled with electron atomic pair distribution function analysis (ePDF) to understand the local order (structure and chemistry) as a function of position in a complex multicomponent system, a hot rolled, Ni-encapsulated, Zr 65 Cu 17.5 Ni 10 Al 7.5 bulk metallic glass (BMG), with a spatial resolution of 3 nm. We show that it is possible to gain insight into the chemistry and chemical clustering/ordering tendency in different regions of the sample, including in the vicinity of nano-scale crystallites that are identified from virtual dark field images and in heavily deformed regions at the edge of the BMG. In addition to simpler analysis, unsupervised machine learning was used to extract partial PDFs from the material, modeled as a quasi-binary alloy, and map them in space. These maps allowed key insights not only into the local average composition, as validated by EELS, but also a unique insight into chemical short-range ordering tendencies in different regions of the sample during formation. The experiments are straightforward and rapid and, unlike spectroscopic measurements, don’t require energy filters on the instrument. We spatially map different quantities of interest (QoI’s), defined as scalars that can be computed directly from positions and widths of ePDF peaks or parameters refined from fits to the patterns. We developed a flexible and rapid data reduction and analysis software framework that allows experimenters to rapidly explore images of the sample on the basis of different QoI’s. The power and flexibility of this approach are explored and described in detail. Because of the fact that we are getting spatially resolved images of the nanoscale structure obtained from ePDFs we call this approach scanning nano-structure electron microscopy (SNEM), and we believe that it will be powerful and useful extension of current 4D-STEM methods.

36 MATERIALS SCIENCE↗
DOE OSTI2023

A seamless approach for evaluating climate models across spatial scales

In regions of the world where topography varies significantly with distance, most global climate models (GCMs) have spatial resolutions that are too coarse to accurately simulate key meteorological variables that are influenced by topography, such as clouds, precipitation, and surface temperatures. One approach to tackle this challenge is to run climate models of sufficiently high resolution in those topographically complex regions such as the North American Regionally Refined Model (NARRM) subset of the Department of Energy’s (DOE) Energy Exascale Earth System Model version 2 (E3SM v2). Although high-resolution simulations are expected to provide unprecedented details of atmospheric processes, running models at such high resolutions remains computationally expensive compared to lower-resolution models such as the E3SM Low Resolution (LR). Moreover, because regionally refined and high-resolution GCMs are relatively new, there are a limited number of observational datasets and frameworks available for evaluating climate models with regionally varying spatial resolutions. As such, we developed a new framework to quantify the added value of high spatial resolution in simulating precipitation over the contiguous United States (CONUS). To determine its viability, we applied the framework to two model simulations and an observational dataset. We first remapped all the data into Hierarchical Equal-Area Iso-Latitude Pixelization (HEALPix) pixels. HEALPix offers several mathematical properties that enable seamless evaluation of climate models across different spatial resolutions including its equal-area and partitioning properties. The remapped HEALPix-based data are used to show how the spatial variability of both observed and simulated precipitation changes with resolution increases. This study provides valuable insights into the requirements for achieving accurate simulations of precipitation patterns over the CONUS. It highlights the importance of allocating sufficient computational resources to run climate models at higher temporal and spatial resolutions to capture spatial patterns effectively. Furthermore, the study demonstrates the effectiveness of the HEALPix framework in evaluating precipitation simulations across different spatial resolutions. This framework offers a viable approach for comparing observed and simulated data when dealing with datasets of varying spatial resolutions. By employing this framework, researchers can extend its usage to other climate variables, datasets, and disciplines that require comparing datasets with different spatial resolutions.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2012

Advances in Rotor Performance and Turbulent Wake Simulation Using DES and Adaptive Mesh Refinement

Time-dependent Navier-Stokes simulations have been carried out for a rigid V22 rotor in hover, and a flexible UH-60A rotor in forward flight. Emphasis is placed on understanding and characterizing the effects of high-order spatial differencing, grid resolution, and Spalart-Allmaras (SA) detached eddy simulation (DES) in predicting the rotor figure of merit (FM) and resolving the turbulent rotor wake. The FM was accurately predicted within experimental error using SA-DES. Moreover, a new adaptive mesh refinement (AMR) procedure revealed a complex and more realistic turbulent rotor wake, including the formation of turbulent structures resembling vortical worms. Time-dependent flow visualization played a crucial role in understanding the physical mechanisms involved in these complex viscous flows. The predicted vortex core growth with wake age was in good agreement with experiment. High-resolution wakes for the UH-60A in forward flight exhibited complex turbulent interactions and turbulent worms, similar to the V22. The normal force and pitching moment coefficients were in good agreement with flight-test data.

Chaderjian, Neal M.↗
DOE OSTI2026

MATEY: multiscale adaptive transformer models for spatiotemporal physical systems

Accurate representation of the multiscale features in spatiotemporal physical systems using vision transformer architectures requires extremely long, computationally prohibitive token sequences. To address this issue, we propose two novel adaptive tokenization schemes that dynamically adjust patch sizes based on local features: one ensures convergent behavior to uniform patch refinement, while the other offers better computational efficiency. Moreover, we present a set of spatiotemporal attention schemes, where the temporal or axial spatial dimensions are decoupled, to evaluate their baseline computational and data efficiencies and to determine whether adaptive tokenization can improve this performance. We assess the performance of the proposed multiscale adaptive model, MATEY, in a sequence of experiments. Compared to a full spatiotemporal attention scheme or a scheme that decouples only the temporal dimension, we find that fully decoupled axial attention is less efficient and expressive, requiring more training time and model parameters to achieve the same accuracy. The experiments on the adaptive tokenization schemes show that, compared to a uniformly refined model, the proposed schemes achieve comparable or improved accuracy at a much lower cost in the tested two-dimensional settings. While the asymptotic analysis suggests the potential for favorable scaling, empirical validation at substantially longer sequence lengths remains to be performed in future work. Finally, we demonstrate in two fine-tuning tasks featuring different physics that models pretrained on PDEBench data outperform the ones trained from scratch, especially in the low data regime with frozen attention.

adaptive tokenization↗
DOE OSTI2024

Heat release surrogates for NH 3 /H 2 /N 2 –air premixed flames

The present study investigates the performance of NH, NH 2 , O-atom, and H-atom as heat release rate (HRR) surrogates for NH 3 /H 2 /N 2 –air premixed flame through simulations. The simulations are conducted across different pressures, reactant inlet temperatures, fuel blend compositions, and equivalence ratios. Cantera is used to simulate one-dimensional (1D) freely propagating flames to investigate the spatial correlations of the species with the HRR. PeleLMeX, a low-Mach direct numerical simulation (DNS) code with Adaptive Mesh Refinement (AMR), is used to simulate two-dimensional (2D) flame-vortex interactions to investigate the temporal correlations including stretch effects. Three different mechanisms (Jiang et al. 2020; Glarborg et al. 2018; Okafor et al. 2018) were considered in the 1D flame simulations, whereas only the Jiang mechanism was considered in the flame-vortex simulations. The HRR surrogate performance for the 2D flames is evaluated at two different locations: (1) the centerline and (2) the flame cusp. The cusp is defined as the region in the flame front with the greatest curvature and the centerline encounters the highest tangential strain rate. The 1D flame results suggest that, although there is not uniformly good spatial correlation for HRR across all flame conditions, NH is the best overall as a HRR surrogate for laminar flames. The 2D flame results, however, suggest that O-atom and H-atom have satisfactory temporal correlations at different conditions—the former for rich flames, the latter for high-pressure flames. Furthermore, these simulations provide guidance to experimental measurements of surrogate HRR markers in unsteady multi-dimensional flames using laser diagnostics to detect species such as NH, O-atom, and H-atom.

Ammonia↗
DOE OSTI2022

Process-based modeling of soil nitrous oxide emissions from United States corn fields under different management and climate scenarios coupled with evaluation using regional estimates

Direct emissions of soil nitrous oxide during a growing season (N 2 O gs ) can be quantified with process-based models considering interactions between management, climate, and soil moisture when key data are available. We used an adapted “parameterized CENTURY/DAYCENT-model” ( p CENTURY) calibrated with crop growth and soil organic matter decay coefficients at the county-level for the estimation of N 2 O gs in the United States Corn Belt. Model estimated N 2 O-emissions from corn-based biofuels scenarios considering crop rotation, fertilizer inputs, tillage, and weather were compared against meta-summary of field observations from 55 studies. Both model and meta-summary ranked N 2 O gs -emissions to be corn > wheat > soybean phase while model likely underestimated cover crop N 2 O gs -emissions. The N 2 O gs -emissions and the associated emission factors (EFs) were modeled and summarized to be greater after anhydrous ammonia than urea application and from conventional tilled than non-tilled fields. Modeled and observed N 2 O gs -emissions after organic and inorganic fertilizer amendment did not differ due to high variability associated with the treatments. However, the organic fertilizer associated EFs were greater according to meta-summary data because of N input rates. Regionalized weather scenarios indicate hotspots for N 2 O gs -emissions can occur where crop N uptake is limited during dry years and in eastern states also during normal or wet seasons. The p CENTURY-derived N 2 O gs EFs (0.91 ± 0.19%) for counties investigated were only slightly lower than literature (1.07 ± 0.57%) or Tier-1 (1%) values. Our preliminary evaluation of regional soil moisture estimates showed reasonable agreement between monthly soil moisture estimates and the North American Soil Moisture Dataset during the growing season, but overestimation of soil moisture in winter-spring can influence the estimates of annual N 2 O emissions so future work is needed to calibrate soil moisture-associated model parameters. Our work provided scenario-based estimates of climate and management impacts on soil N 2 O gs -emissions together with valuable spatial insights into EFs that will be improved by more accurate information of fertilizer inputs and more temporally refined model evaluation.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1993

Source term evaluation for combustion modeling

A modification is developed for application to the source terms used in combustion modeling. The modification accounts for the error of the finite difference scheme in regions where chain-branching chemical reactions produce exponential growth of species densities. The modification is first applied to a one-dimensional scalar model problem. It is then generalized to multiple chemical species, and used in quasi-one-dimensional computations of shock-induced combustion in a channel. Grid refinement studies demonstrate the improved accuracy of the method using this modification. The algorithm is applied in two spatial dimensions and used in simulations of steady and unsteady shock-induced combustion. Comparisons with ballistic range experiments give confidence in the numerical technique and the 9-species hydrogen-air chemistry model.

Sussman, Myles A.↗