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At least 1,117 records · Page 62
All sourcesNASA NTRSDOE OSTI
DOE OSTI2013

Review of cyclic experiments performed on PBX9501

This report briefly summarizes an interesting set of experiments performed on PBX9501 in FY13. It also describes the use of the experimental data in a constitutive model development program. The experiments were requested as a follow-on to a set of cyclic compression experiments performed by Darla Thompson in 2008. Thompson originally performed the experiments to demonstrate a capability and to stimulate discussions on what experimental data W13 needed. Those experiments proved crucial in demonstrating that the material exhibited permanent deformation after removal of load, viscoelastic recovery, and some form of damage. Further experiments were requested to flesh out a viscoelastic-viscoplastic-viscodamage model.

42 ENGINEERING↗
DOE OSTI2016

Atmospheric {sup 41}Ar Plume Tracking of the UF Training Reactor Using a Large-Volume NaI Detector

The ability to track and monitor gaseous radioactive materials is important in the event of a radioactive release such as from a nuclear power plant accident, weapons testing, or other unintended release scenarios. The International Monitoring System (IMS) is currently in place to monitor for weapons testing and has been used to monitor nuclear power plant accidents. However, only 80 radionuclide stations for the IMS exist in the world and are stationary, limiting the resolution of any radioactive plumes detected. Furthermore, the IMS radionuclide stations are designed to be sensitive specifically to atmospheric radio-xenon and no other radionuclides. Historically, monitoring radioactive releases has been limited to the detection of radio-xenon and radio-krypton, both arising as fission products from nuclear fuel. After the accident at Three Mile Island Unit 2, scientists were interested in finding the dose the public received from released radioactive material. This was achieved by analyzing radiation monitors in the exhaust stack and filters within the reactor building. furthermore, a series of 20 thermoluminescent dosimeters (TLD's), 8 air sampling station positioned around Three Mile Island, and a helicopter survey which used a NaI(Tl) detector array provided data on radionuclides, specifically {sup 137}Cs, that escaped the confines of the reactor building. The TLD's and air sampling stations were stationary, and therefore limited the resolution of the radioactive release plume. The helicopter survey using the NaI detectors was limited by the technology available at the time. The NaI detector array output was compressed from 1024 channels to 256 channels, limiting the energy resolution of the spectral data. The helicopter used a microwave ranging system to establish position. Since this survey was taken in October of 1982, advancements in technology allow spectral data to be saved in its full 1024 channel format and the advent of GPS can give a more accurate account of the detector position. An updated mobile system for tracking a radioactive release would help to alleviate these issues as well as gain the ability to track a radioactive release in real-time. We investigate the feasibility of mobile tracking through study and measurement of the {sup 41}Ar plume released from the University of Florida Training Reactor (UFTR) research reactor. We use a large-volume NaI(Tl) detector placed on the roof near the reactor. This detector may also be placed and moved on a cart to survey the area surrounding the reactor. We compare the spectral data taken when the reactor is running at full power to the background to analyze the effectiveness of the detector at identifying atmospheric {sup 41}Ar. Finally we discuss the implications of these measurements with regards to validation of plume models and the capability to track releases over a localized area from the source. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2016

In situ and in-transit analysis of cosmological simulations

Abstract Modern cosmological simulations have reached the trillion-element scale, rendering data storage and subsequent analysis formidable tasks. To address this circumstance, we present a new MPI-parallel approach for analysis of simulation data while the simulation runs, as an alternative to the traditional workflow consisting of periodically saving large data sets to disk for subsequent ‘offline’ analysis. We demonstrate this approach in the compressible gasdynamics/ N -body code Nyx, a hybrid $\mbox{MPI}+\mbox{OpenMP}$ MPI + OpenMP code based on the BoxLib framework, used for large-scale cosmological simulations. We have enabled on-the-fly workflows in two different ways: one is a straightforward approach consisting of all MPI processes periodically halting the main simulation and analyzing each component of data that they own (‘ in situ ’). The other consists of partitioning processes into disjoint MPI groups, with one performing the simulation and periodically sending data to the other ‘sidecar’ group, which post-processes it while the simulation continues (‘in-transit’). The two groups execute their tasks asynchronously, stopping only to synchronize when a new set of simulation data needs to be analyzed. For both the in situ and in-transit approaches, we experiment with two different analysis suites with distinct performance behavior: one which finds dark matter halos in the simulation using merge trees to calculate the mass contained within iso-density contours, and another which calculates probability distribution functions and power spectra of various fields in the simulation. Both are common analysis tasks for cosmology, and both result in summary statistics significantly smaller than the original data set. We study the behavior of each type of analysis in each workflow in order to determine the optimal configuration for the different data analysis algorithms.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Hydrogel-assisted self-healing of biomineralized living building materials

Living building materials (LBMs) are an emergent class of structural materials that leverage the biomineralization capability of microorganisms within sand-hydrogel scaffolds to produce living, load-bearing structures. Here we produced LBMs using a physically crosslinkable sand-hydrogel scaffold and two microorganisms with different biomineralization pathways - Synechococcus sp. PCC 7002 (photosynthetic) and S. pasteurii (ureolytic) - and investigated their self-healing capacity. Our results reveal that both Synechococcus sp. PCC 7002 and S. pasteurii demonstrated exceptional viability within all LBMs for more than 20 days. Damaged LBMs containing Synechococcus sp. PCC 7002 exhibited 103% and 112% of their original compressive and flexural strengths, respectively, after three days of healing at 50% relative humidity (RH) (i.e., ambient conditions). In contrast, LBMs containing S. pasteurii exhibited 71% and 66% of their original compressive and flexural strengths, respectively, after three days of healing at 50% RH. The compressive and flexural strengths of all LBMs rebounded to 93-100% after seven days of healing at 50% RH. Data substantiate that the self-healing ability of the hydrogel plays a critical role in facilitating healing of LBMs, as evidenced by the 82-118% rebounds in compressive and flexural strengths by the sand-hydrogel scaffold alone after three or seven days of healing at 50% RH. Healing was less effective at 100% RH for all LBMs investigated herein.

36 MATERIALS SCIENCE↗
DOE OSTI2014

The influence of pressure on the structure of a 2D uranium(VI) carboxyphosphonoate compound

We report the first quantitative analysis of the structural evolution of a uranyl bearing coordination polymer in response to pressure. The material that is central to this study, (UO{sub 2})(O{sub 3}PCH{sub 2}CO{sub 2}H) (1), is constructed from rigid 2D inorganic layers comprising edge sharing UO{sub 7} pentagonal bipyramids cross-linked by [PO{sub 3}(COOH)]{sup 2−} anions. Strong hydrogen bonding interactions exist between the pendent carboxylic acid groups on adjacent layers. Under pressure, 1 exhibits compressional behaviour primarily in the direction perpendicular to the inorganic layers, which is aided by a reduction in the interlayer distance and shifting of the layers with respect to each other. The bulk modulus for the 2D compound 1 is unexpectedly high [18.1(1) GPa] and is within the range reported for 3D CPs assembled from Zn{sup II} cations and inflexible imidazolate anions, and is at the lower end of the range of moduli observed for aluminosilicate zeolites (19–59 GPa). - Graphical Abstract: The compression mechanism and elastic constants for a 2D Uranium(VI) carboxyphosphonoate compound are reported. - Highlights: • The response to pressure of a uranium carboxyphosphonoate compound has been studied. • High-pressure single-crystal XRD data for this 2D uranium compound were collected. • Elastic constants for this material have been determined. • The compression mechanism for the compound has been elucidated.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Thermal field reconstruction and compressive sensing using proper orthogonal decomposition

Model order reduction allows critical information about sensor placement and experiment design to be distilled from raw fluid mechanics simulation data. In many cases, sensed information in conjunction with reduced order models can also be used to regenerate full field variables. In this paper, a proper orthogonal decomposition (POD) inferencing method is extended to the modeling and compressive sensing of temperature, a scalar field variable. The method is applied to a simulated, critically stable, incompressible flow over a heated cylinder (Re = 1000) with Prandtl number varying between 0.001 and 50. The model is trained on pressure and temperature data from simulations. Field reconstructions are then generated using data from selected sensors and the POD model. Finally, the reconstruction error is evaluated across all Prandtl numbers for different numbers of retained modes and sensors. The predicted trend of increasing reconstruction accuracy with decreasing Prandtl number is confirmed and a Prandtl number/sensor count error matrix is presented.

Matulis, John↗
DOE OSTI2015

Fast and low-dose computed laminography using compressive sensing based technique

Computed laminography (CL) is well known for inspecting microstructures in the materials, weldments and soldering defects in high density packed components or multilayer printed circuit boards. The overload problem on x-ray tube and gross failure of the radio-sensitive electronics devices during a scan are among important issues in CL which needs to be addressed. The sparse-view CL can be one of the viable option to overcome such issues. In this work a numerical aluminum welding phantom was simulated to collect sparsely sampled projection data at only 40 views using a conventional CL scanning scheme i.e. oblique scan. A compressive-sensing inspired total-variation (TV) minimization algorithm was utilized to reconstruct the images. It is found that the images reconstructed using sparse view data are visually comparable with the images reconstructed using full scan data set i.e. at 360 views on regular interval. We have quantitatively confirmed that tiny structures such as copper and tungsten slags, and copper flakes in the reconstructed images from sparsely sampled data are comparable with the corresponding structure present in the fully sampled data case. A blurring effect can be seen near the edges of few pores at the bottom of the reconstructed images from sparsely sampled data, despite the overall image quality is reasonable for fast and low-dose NDT.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

Compressibility effects in the shear layer over a rectangular cavity

we studied the influence of compressibility on the shear layer over a rectangular cavity of variable width in a free stream Mach number range of 0.6–2.5 using particle image velocimetry data in the streamwise centre plane. As the Mach number increases, the vertical component of the turbulence intensity diminishes modestly in the widest cavity, but the two narrower cavities show a more substantial drop in all three components as well as the turbulent shear stress. Furthermore, this contrasts with canonical free shear layers, which show significant reductions in only the vertical component and the turbulent shear stress due to compressibility. The vorticity thickness of the cavity shear layer grows rapidly as it initially develops, then transitions to a slower growth rate once its instability saturates. When normalized by their estimated incompressible values, the growth rates prior to saturation display the classic compressibility effect of suppression as the convective Mach number rises, in excellent agreement with comparable free shear layer data. The specific trend of the reduction in growth rate due to compressibility is modified by the cavity width.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Multi-stage heat release of multi-component fuels: Insights and implications for advanced engine operation

Multi-stage heat release (MSHR) is a unique phenomenon typically seen in lean/diluted and low- to intermediate-temperature combustion. Despite its relevance to advanced engine operation, the MSHR of multi-component fuels has barely been quantified. This study aims to characterize the MSHR of multi-component fuels in a rapid compression machine (RCM) at conditions representative of advanced combustion engines. New experimental data are first reported in the RCM at an equivalence ratio of 0.4, pressure of 60 bar and temperatures from 702 to 795 K for a research grade, multi-component gasoline surrogate, termed PACE-20. Here, experiments confirm the existence of MSHR for PACE-20 at all temperatures, and reveal the strong inhibiting effect of temperature on MSHR, where increasing temperature inhibits MSHR by suppressing first stage heat release and promoting second and third stage heat release. A detailed chemical kinetic model is also adopted to model the experiments, with good agreement observed. The response of MSHR characteristics to changes in different engine operating parameters (i.e., temperature, pressure, equivalence ratio and CO 2 dilution level) and fuel compositions (i.e., mole fraction of n-pentane, n-heptane, isooctane, cyclopentane, 1-hexene, ethanol and aromatics in PACE-20) is further evaluated via statistical analysis coupling quasi-random sampling, extensive computer experiments and high-dimensional model representation. The change in MSHR is characterized through 8 quantities of interest (QOIs), i.e., duration and extent of each heat release stage, and their standard deviations. The analysis highlights the dependence of the QOIs on the individual parameters as well as their interplays, with temperature exhibiting the strongest impact among all parameters. Furthermore, it is demonstrated that if MSHR is to be facilitated and combustion phasing is to be extended to enable engine operation at higher compression ratios, it is recommended to operate the engine at low intake temperatures, boosted intake pressures and high CO 2 dilutions (i.e., high EGR levels) with gasoline fuels containing more n-pentane and less aromatics.

42 ENGINEERING↗
DOE OSTI2020

(U) PRAD0697 & PRAD0698: Complex Loading of CeO₂ Powder

Cerium(IV) oxide (CeO₂) powder is shock compressed using the Precision High Energy-density Liner Implosion eXperiment (PHELIX) platform. Experimental results are compared against several modeling approaches. Compaction behavior is best captured with a P-∝ model, which calculates CeO₂ powder bulk densities within 80-99% of experimental values but overpredicts densi cation at the cylindrical target's outer radius and center by up to 20%. Preliminary calculations suggest that accuracy could be increased with the inclusion of a coupled strength model. Several common computational modeling approaches for the shock compression response of granular materials and the magnetohydrodynamic (MHD) force upon the impactor/liner in pulsed power compression experiments are investigated and analyzed for their validity. The Bi-linear Ramp, P-∝ PACXP, and P-∝ Menikoff-Kober continuum compaction models are calibrated to planar impact Hugoniot data for CeO₂ powder and used to predict the powder's shock compaction response under non-planar shock wave compression. MHD calculations of the PHELIX pulsed power driver are performed using an idealized resistor-inductor-capacitor (RLC) circuit calibrated to previous experiments. All simulations are performed using the LANL code FLAG. Two validation experiments are computationally designed using the calibrated compaction and circuit models, executed using the PHELIX platform on CeO₂ targets with initial porous densities of 3.95 and 4.03 g/cm³, measured with proton radiography, and analyzed against the model predictions. The two P-∝ models more accurately describe CeO₂ powder densi cation than the Bi-linear Ramp model. However, the two P-∝ models overpredict bulk density of the shock compressed CeO₂ powder by up to 20% when the appropriate impact velocities are applied. MHD calculations for both validation experiments underpredict liner impact velocities by 4-11% when using the idealized RLC circuit model calibrated to previous experiments. Compensating underpredictions of impact velocity and overpredictions of powder densication lead to a false accuracy in pre-shot calculations compared to experimental data. To improve correlation between simulations and experiments, the following improvements are suggested: 1. A coupled strength model for CeO₂ powder that updates strength as a function of porosity and applied stress. 2. An improved MHD circuit model that more accurately captures the PHELIX machine.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Utilizing computer vision and artificial intelligence algorithms to predict and design the mechanical compression response of direct ink write 3D printed foam replacement structures

Additive Manufacturing (AM) of porous polymeric materials, such as foams, recently became a topic of intensive research due their unique combination of low density, impressive mechanical properties, and stress dissipation capabilities. Conventional methods for fabricating foams rely on complex and stochastic processes, making it challenging to achieve precise architectural control of structured porosity. In contrast, AM provides access to a wide range of printable materials, where precise spatial control over structured porosity can be modulated during the fabrication process enabling the production of foam replacement structures (FRS). Current approaches for designing FRS are based on intuitive understanding of their properties or an extensive number of finite element method (FEM) simulations. These approaches, however, are computationally expensive and time consuming. As such, in this work, we present a novel methodology for determining the mechanical compression response of direct ink write (DIW) 3D printed FRS using a simple cross-sectional image. By obtaining measurement data for a relatively small number of samples, an artificial neural network (ANN) was trained, and a computer vision algorithm was used to make inferences about foam compression characteristics from a single cross-sectional image. Finally, a genetic algorithm (GA) was used to solve the inverse design problem, generating the AM printing parameters that an engineer should use to achieve a desired compression response from a DIW printed FRS. The methods developed herein present an avenue for entirely autonomous design and analysis of additively manufactured structures using artificial intelligence.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Misr: Miniature Ignition Screening Rapid Compression Machine for Kinetic Measurements of Novel Fuels (Final Report)

High throughput ignition screening would be useful for evaluating fuels before scaled production. One method for doing this involves generating a map of ignition delay times over different conditions for each fuel blend. Constant condition ignition delay time maps can be used to estimate ignition for engines in prescribed thermodynamic trajectories. A Miniaturized Ignition Screening Rapid Compression Machine (MISR) has been developed and built at the University of Illinois Chicago (UIC) intending to generate those constant condition ignition delay time maps for low temperature chemistry relevant conditions. Some design features include a bellows-actuated driver section, which is lighter compared to other RCM designs, an adjustable brake section, and full optical access. The setup was designed to achieve reaction conditions (T > 600K and P < 100 bar with repetition rates of about 8 seconds per experiment). These conditions were meant to be relevant to low-to-intermediate temperature auto-ignition and for generation of data for developing relevant chemical kinetics models or ignition maps. Because of the compression characteristics and the heat loss characteristics of the MISR, the apparatus currently tests higher temperatures over shorter test times than what would be desirable, however there are some pathways to improved compression characteristics as detailed in this report. A detailed description of the MISR design and its operating mechanism is discussed. The team faced several challenges and setbacks in the construction and commissioning of the MISR, and those are highlighted, along with the modifications that were performed to get the MISR operational. To demonstrate the performance characteristics of the MISR, limited ignition delay experiments were conducted for ethanol fuel at different equivalence ratios (Φ), and those results were usable, but again test a higher temperature and shorter ignition delay time than initially intended.

02 PETROLEUM↗
DOE OSTI2020

Discrete element modeling of switchgrass particles under compression and rotational shear

Switchgrass is a perennial herbaceous plant regarded as a biomass energy crop in the United States for its highadaptability and yield potential. Processing and handling of switchgrass particles are challenging due to the erratic mechanical and flow behavior originating from their intrinsic particulate properties. Here, we present a bonded-sphere discrete element model designed specifically for switchgrass particles. The model simultaneously captures three key particulate features, i.e., fibrous particle shapes, a wide range of particle sizes, and particle deformability. Realistic yet computationally efficient particle shape templates are created based on the image analysis data of switchgrass specimens. A fitting procedure is proposed to ensure both the particle width and length distributions are captured, a unique requirement for fibrous particles. Two full-scale numerical models, i.e., a uniaxial compression model and a Schulze ring shear model, are developed using information fromphysical experiments. The model is calibrated using experimental data of chopped-small switchgrass specimens, and then, is validated using data of chopped-large specimens in both compression and ring-shear tests. Numerical results show that the numerical models capture bulk densities accurately (with an error of 3%) while slightly underestimate the bulk friction angle. Furthermore, an extensive sensitivity analysis reveals that (1) switchgrass particles with rougher edges (due to different processing techniques) exhibit a higher shear strength and a lower flowability; (2) stiffer particles yield a lower bulk density (up to 21% lower) compared to more deformable particles, indicating particle deformability should be incorporated when modeling biomass flow in a preprocessing system.

09 BIOMASS FUELS↗
DOE OSTI2018

Insights into Engine Knock: Comparisons of Knock Metrics across Ranges of Intake Temperature and Pressure in the CFR Engine

Of late there has been a resurgence in studies investigating parameters that quantify combustion knock in both standardized platforms and modern spark-ignition engines. However, it is still unclear how metrics such as knock (octane) rating, knock onset, and knock intensity are related and how fuels behave according to these metrics across a range of conditions. As part of an ongoing study, the air supply system of a standard Cooperative Fuel Research (CFR) F1/F2 engine was modified to allow mild levels of intake air boosting while staying true to its intended purpose of being the standard device for American Society for Testing and Materials (ASTM)-specified knock rating or octane number tests. For instance, the carburation system and intake air heating manifold are not altered, but the engine was equipped with cylinder pressure transducers to enable both logging of the standard knockmeter readout and state-of-the-art indicated data. For this study, the engine was operated using primary reference fuel 90 (PRF90) at 600 rpm, first following the procedures of the ASTM D2699 research octane number test protocol in order to define the geometric compression ratio set point for standard knock number. Thereafter, compression ratio sweeps were conducted at intake temperatures ranging from 30 to 150°C and intake air boost extending from 0 to 0.3 bar above ambient. The resulting operating map provided a broad envelope of compressed in-cylinder conditions relevant to modern spark-ignition engines. Detailed analysis of the indicated data highlighted a poor correlation between established knock intensity metrics and the knockmeter reading, which is used to characterize a fuel’s octane number. It was further found that the auto-ignition characteristics of PRF90 could be perturbed by means of intake air boosting and heating without being captured by the knockmeter reading.

Rockstroh, Toby↗
DOE OSTI2017

Superelastic and micaceous deformation in the intermetallic compound CaFe 2 As 2

Single-crystalline intermetallic compound CaFe 2 As 2 are known to exhibit both superelasticity and micaceous plasticity, but these phenomena have not been studied in detail. Here we report a study of the elastic and plastic deformation behaviors for CaFe 2 As 2 single crystals grown in Sn-flux solution. The anisotropic mechanical response has been studied using micropillar compression tests performed in-situ within a scanning electron microscope. Further, these data are compared with density functional theory calculations to develop an understanding of micaceous plasticity in terms of strongly anisotropic generalized stacking fault energies. The results of this work will offer design guidelines to produce mechanically robust superelastic structures.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Data-driven closure modeling for hypersonic turbulent flows

The Reynolds-averaged Navier–Stokes (RANS) equations remain a workhorse technology for simulating compressible fluid flows of practical interest. Due to model-form errors, however, RANS models can yield erroneous predictions that preclude their use on mission-critical problems. This report summarizes work performed from FY22-FY24 focused on improving RANS models for hypersonic flows using data-driven modeling and scientific machine learning. In this work we: 1. Investigate the current capabilities of RANS models in Sandia’s parallel aerodynamics and re-entry code (SPARC) for hypersonic flows with a focus on shock boundary layer interactions (SBLIs), 2. Assess several established corrections that exist in the literature aimed at improving predictions for SBLIs, 3. Develop improved models for the Reynolds stress tensor using tensor-basis neural networks, 4. Develop a neural-network-based variable turbulent Prandtl number model to reduce errors in wall heating in SBLIs. 5. Begin future investigations including employing the LIFE framework to improve wall heating predictions in SBLIs as well as the ensemble Kalman filter. We find that current RANS models in SPARC are deficient for complex SBLI flows. In particular, no current model jointly predicts wall heat flux, wall shear stress, and wall pressure with reasonable accuracy. Existing corrections help, but do not alleviate this issue altogether. The development of improved models for the Reynolds stress tensor via tensor-basis neural networks results in more predictive RANS models across a suite of low-speed and high-speed cases. For hypersonic boundary layers, the inclusion of the wall-normal Reynolds stress via TBNNs has an appreciable impact on the wall-normal momentum balance and wall quantities. However, we find that improvements to the Reynolds stress tensor do not address the over-prediction in wall heat flux in SBLIs. We find that a neural-network-based variable turbulent Prandtl number model systematically and substantially improves wall heating predictions for a range of SBLI cases.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Broom: application for non-redundant storage of high throughput sequencing data

Abstract Motivation The data generation capabilities of high throughput sequencing (HTS) instruments have exponentially increased over the last few years, while the cost of sequencing has dramatically decreased allowing this technology to become widely used in biomedical studies. For small labs and individual researchers, however, storage and transfer of large amounts of HTS data present a significant challenge. The recent trends in increased sequencing quality and genome coverage can be used to reconsider HTS data storage strategies. Results We present Broom, a stand-alone application designed to select and store only high-quality sequencing reads at extremely high compression rates. Written in C++, the application accepts single and paired-end reads in FASTQ and FASTA formats and decompresses data in FASTA format. Availability and implementation C++ code available at https://scsb.utmb.edu/labgroups/fofanov/broom.asp. Supplementary information Supplementary data are available at Bioinformatics online.

Albayrak, Levent↗
DOE OSTI2022

Analysis of Compressibility Effects and Nonlinear Property Variations in a Supercritical CO2 Mixing Layer

Calculations are performed using the large eddy simulation technique to qualitatively assess the effects of fluid compressibility and thermodynamic nonlinearities on the dynamics of a supercritical flow field. Resulting data are also used to interrogate instantaneous subfilter-scale fields, as modeled by the mixed-dynamic Smagorinsky closure and gradient diffusion model. A three-dimensional wall-resolved calculation of a spatially evolving mixing layer composed solely of carbon dioxide is performed. This is followed by a coarse grid calculation to examine model performance as a function of resolution. Theoretical analysis indicates that the partial derivatives of density with respect to pressure and temperature are important modulators of the temperature and pressure field evolution, respectively. Results pertaining to subfilter velocity-velocity and velocity-temperature fields indicate that the models are most stressed in the regions where compressibility and thermo-fluid nonlinearities dominate the physics.

42 ENGINEERING↗