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At least 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
NASA NTRS2022

Application Table: A Bridge Connecting the Designing “With-The-Material” and “The-Material” Paradigms

Over the last few decades, advances in high-performance computing, new material characterization methods, and, more recently, an emphasis on integrated computational materials engineering (ICME) have been a catalyst for multiscale modeling and simulation-based design of materials and structures in the aerospace industry. In 2016 NASA sponsored a 2040 Vision study (which appeared in 2018) to define the potential 25-year future state required for integrated multiscale modeling of materials and systems (e.g., load-bearing structures) to accelerate the pace and reduce the expense of innovation in future aerospace and aeronautical systems. The study envisions a cyber-physical-social ecosystem comprised of experimentally verified and validated (V & V) computational models, tools, and techniques, along with the associated digital tapestry, that impacts the entire supply chain to enable cost-effective, rapid, and revolutionary design of “fit-for-purpose” materials, components, and systems. Consequently, the development of a robust information management system that incorporates (across the full life cycle) both experimental (real data) and virtual data resulting from the application of various simulation tools (at single or multiple length scales), therefore enabling the virtual design and optimization of materials throughout their processing – internal structure – property – performance envelope, has become critical. This need is also fueled by the demands for higher efficiency in material testing; consistency, quality, and traceability of data; product design; engineering analysis; as well as control of access to proprietary or sensitive information. This is particularly true when attempting to merge ICME practices with recent additive manufacturing technology which will enable production of the resulting 2040 Vision material and structural designs. At NASA Glenn Research Center we are exploring the future of material science through the use of novel characterization methodologies, high performance computing, and recently an emphasis on integrated computational materials engineering (ICME). Herein, recent efforts to incorporate an Application Table within NASA Glenn Research Center’s ICME Granta MI database is presented. The goal is to provide a place where material and structural application information/requirements can be linked so as to marry the “design the-material” and the “design-with-material” paradigms and thereby enable application-driven design and optimization of materials and structures by providing a central location that links material processing at various length scales to the application’s performance requirements. This paper discusses the specifics of this Application Table as well as best practices and key principles for the development of a robust materials information management system to enable the 2040 Vision integrated materials and structures ecosystem. Furthermore, it presents the intended role of the Application Table in the future of ICME design of “fit-for-purpose” materials, showing the need for a well-established framework that can successfully bridge the gap between the design “the material” and design “with-the-material” paradigms.

Materials↗
NASA NTRSDate not supplied

Application Table: A Bridge Connecting the Designing “With-the-Material” and “the-Material”

Over the last few decades, advances in high-performance computing, new material characterization methods, and, more recently, an emphasis on integrated computational materials engineering (ICME) have been a catalyst for multiscale modeling and simulation-based design of materials and structures in the aerospace industry. In 2016 NASA sponsored a 2040 Vision study (which appeared in 2018) to define the potential 25-year future state required for integrated multiscale modeling of materials and systems (e.g., load-bearing structures) to accelerate the pace and reduce the expense of innovation in future aerospace and aeronautical systems. The study envisions a cyber-physical-social ecosystem comprised of experimentally verified and validated (V & V) computational models, tools, and techniques, along with the associated digital tapestry, that impacts the entire supply chain to enable cost-effective, rapid, and revolutionary design of “fit-for-purpose” materials, components, and systems. Consequently, the development of a robust information management system that incorporates (across the full life cycle) both experimental (real data) and virtual data resulting from the application of various simulation tools (at single or multiple length scales), therefore enabling the virtual design and optimization of materials throughout their processing – internal structure – property – performance envelope, has become critical. This need is also fueled by the demands for higher efficiency in material testing; consistency, quality, and traceability of data; product design; engineering analysis; as well as control of access to proprietary or sensitive information. This is particularly true when attempting to merge ICME practices with recent additive manufacturing technology which will enable production of the resulting 2040 Vision material and structural designs. At NASA Glenn Research Center we are exploring the future of material science through the use of novel characterization methodologies, high performance computing, and recently an emphasis on integrated computational materials engineering (ICME). Herein, recent efforts to incorporate an Application Table within NASA Glenn Research Center’s ICME Granta MI database is presented. The goal is to provide a place where material and structural application information/requirements can be linked so as to marry the “design the-material” and the “design-with-material” paradigms and thereby enable application-driven design and optimization of materials and structures by providing a central location that links material processing at various length scales to the application’s performance requirements. This paper discusses the specifics of this Application Table as well as best practices and key principles for the development of a robust materials information management system to enable the 2040 Vision integrated materials and structures ecosystem. Furthermore, it presents the intended role of the Application Table in the future of ICME design of “fit-for-purpose” materials, showing the need for a well-established framework that can successfully bridge the gap between the design “the material” and design “with-the-material” paradigms.

Materials↗
DOE OSTI2025

Solute clustering in polycrystals: Unveiling the interplay of grain boundary junction and long-range solute attraction effects

Spectral analysis of local atomic environments has become a powerful tool for studying solute atom segregation and interactions at grain boundaries in nanocrystalline alloys. When applied to individual grain boundaries, the spectral analysis has shown that solute-solute interaction can be either attractive or repulsive, with long-range relative attraction enhancing the likelihood for solute atoms to begin clustering. In this article, we combine this analysis with a new grain-boundary structure descriptor based on grain-boundary atom coordination, to investigate the impact of grain-boundary junctions on solute atom segregation in polycrystals. Specifically, we systematically characterize the tendency of solute clusters to begin forming at various types of ordinary grain boundaries, triple junctions, and high-order junctions in Ag polycrystals containing either Ni or Cu solute atoms. Our findings demonstrate that the formation of solute clusters at grain boundaries is primarily driven by long-range relative solute attraction, rather than short-range solute-solute interactions. Furthermore, this effect is most pronounced near grain-boundary junctions. Our study highlights the multiscale nature of solute segregation at crystalline interfaces and provides new insights into the complex phenomena governing heterogeneous solute segregation in grain-boundary networks.

Grain-boundary junction↗
NASA NTRS2006

Modeling the Self-organized Critical Behavior of the Plasma Sheet Reconnection Dynamics

Analyses of Polar UVI auroral image data reviewed in our other presentation at this meeting (V. Uritsky, A. Klimas) show that bright night-side high-latitude UV emissions exhibit so many of the key properties of systems in self-organized criticality (SOC) that an alternate interpretation has become virtually impossible. It is now necessary to find and model the source of this behavior. We note that the most common models of self-organized criticality are numerical sandpiles. These are, at root, models that govern the transport of some quantity from a region where it is loaded to another where it is unloaded. Transport is enabled by the excitation of a local threshold instability; it is intermittent and bursty, and it exhibits a number of scale-free statistical properties. Searching for a system in the magnetosphere that is analogous and that, in addition, is known to produce auroral signatures, we focus on the reconnection dynamics of the plasma sheet. In our previous work, a driven reconnection model has been constructed and has been under study. The transport of electromagnetic (primarily magnetic) energy carried by the Poynting flux into the reconnection region of the model has been examined. All of the analysis techniques, and more, that have been applied to the auroral image data have also been applied to this Poynting flux. Here, we report new results showing that this model also exhibits so many of the key properties of systems in self-organized criticality that an alternate interpretation is implausible. Further, we find a strong correlation between these key properties of the model and those of the auroral UV emissions. We suggest that, in general, the driven reconnection model is an important step toward a realistic plasma physical model of self-organized criticality and we conclude, more specifically, that it is also a step in the right direction toward modeling the multiscale reconnection dynamics of the magnetotail.

Klimas, Alex↗
NASA NTRS2006

Modeling the Self-organized Critical Behavior of Earth's Plasma Sheet Reconnection Dynamics

Analyses of Polar UVI auroral image data show that bright night-side high-latitude W emissions exhibit so many of the key properties of systems in self-organized criticality that an alternate interpretation has become virtually impossible. These analyses will be reviewed. It is now necessary to find and model the source of this behavior. We note that the most common models of self-organized criticality are numerical sandpiles. These are, at root, models that govern the transport of some quantity from a region where it is loaded to another where it is unloaded. Transport is enabled by the excitation of a local threshold instability; it is intermittent and bursty, and it exhibits a number of scale-free statistical properties. Searching for a system in the magnetosphere that is analogous and that, in addition, is known to produce auroral signatures, we focus on the reconnection dynamics of the magnetotail plasma sheet. In our previous work, a driven reconnection model has been constructed and has been under study. The transport of electromagnetic (primarily magnetic) energy carried by the Poynting flux into the reconnection region of the model has been examined. All of the analysis techniques (and more) that have been applied to the auroral image data have also been applied to this Poynting flux. New results will be presented showing that this model also exhibits so many of the key properties of systems in self-organized criticality that an alternate interpretation is implausible. A strong correlation between these key properties of the model and those of the auroral UV emissions will be demonstrated. We suggest that, in general, the driven reconnection model is an important step toward a realistic plasma physical model of self-organized criticality and we conclude, more specifically, that it is also a step in the right direction toward modeling the multiscale reconnection dynamics of the magnetotail.

Klimas, Alexander J.↗
NASA NTRSDate not supplied

Multiscale Mesh Adaptation for Transonic Aeroelastic Flutter Problems

This work applies multiscale mesh adaptation with refine to reduce spatial discretization error of aeroelastic computational fluid dynamics (CFD) simulations. Benchmark flutter models, such as the pitch and plunge NACA64A-010 airfoil and the benchmark supercritical wing, are studied with both a linearized frequency-domain solver and time-marching CFD coupled to a modal structural solver in FUN3D. The undeformed NASA Common Research Model (CRM), an aeroelastic jig shape variant of the CRM, is also studied with the linearized frequency-domain approach. For these cases, the adaptation process converges to comparable flutter predictions to hand-generated meshes but with smaller node counts. However the additional disciplines of the linearized frequency-domain analysis, the mesh deformation, and the unsteady finite-volume solver create robustness challenges that need to be addressed before it can be applied as a fully automated process for complex transonic aeroelastic problems. In particular, negative volumes are observed to be an issue for FUN3D’s linear elasticity mesh deformation solver when moving the adapted meshes.

Aeroelasticity↗
NASA NTRS2006

NAVIGATION PERFORMANCE IN HIGH EARTH ORBITS USING NAVIGATOR GPS RECEIVER

NASA GSFC has developed a GPS receiver that can acquire and track GPS signals with sensitivity significantly lower than conventional GPS receivers. This opens up the possibility of using GPS based navigation for missions in high altitude orbit, such as Geostationary Operational Environmental Satellites (GOES) in a geostationary orbit, and the Magnetospheric MultiScale (MMS) Mission, in highly eccentric orbits extending to 12 Earth radii and higher. Indeed much research has been performed to study the feasibility of using GPS navigation in high Earth orbits and the performance achievable. Recently, GSFC has conducted a series of hardware in-the-loop tests to assess the performance of this new GPS receiver in various high Earth orbits of interest. Tracking GPS signals to down to approximately 22-25 dB-Hz, including signals from the GPS transmitter side-lobes, steady-state navigation performance in a geostationary orbit is on the order of 10 meters. This paper presents the results of these tests, as well as sensitivity analysis to such factors as ionosphere masks, use of GPS side-lobe signals, and GPS receiver sensitivity.

Bamford, William↗
NASA NTRSDate not supplied

Multiscale Simulation of Deployable Composite Structures

In this paper, a multiscale simulation method for analyzing deployable composite structures is presented. Effective shell properties of the composites are obtained based on Mechanics of Structure Genome (MSG) homogenization, and then implemented into a user-subroutine UGENS for structural simulation with shell elements in Abaqus. The column bending test(CBT) of a flat thin flexure and lenticular composite boom in a simplified deployer structure are studied for demonstration. A viscoelastic material model with direct integration is adopted in this paper. The CBT simulation shows good agreement with experiments during relaxation, while errors are observed when comparing residual deformation. It is shown that this CBT model can be calibrated to CBT test results. For the lenticular boom analysis, the complete process of flattening, coiling, stowage, deployment and recovery is simulated with the viscoelastic shell model.

Finite element analysis↗
NASA NTRS2006

The Atlanta Urban Heat Island Mitigation and Air Quality Modeling Project: How High-Resoution Remote Sensing Data Can Improve Air Quality Models

The Atlanta Urban Heat Island and Air Quality Project had its genesis in Project ATLANTA (ATlanta Land use Analysis: Temperature and Air quality) that began in 1996. Project ATLANTA examined how high-spatial resolution thermal remote sensing data could be used to derive better measurements of the Urban Heat Island effect over Atlanta. We have explored how these thermal remote sensing, as well as other imaged datasets, can be used to better characterize the urban landscape for improved air quality modeling over the Atlanta area. For the air quality modeling project, the National Land Cover Dataset and the local scale Landpro99 dataset at 30m spatial resolutions have been used to derive land use/land cover characteristics for input into the MM5 mesoscale meteorological model that is one of the foundations for the Community Multiscale Air Quality (CMAQ) model to assess how these data can improve output from CMAQ. Additionally, land use changes to 2030 have been predicted using a Spatial Growth Model (SGM). SGM simulates growth around a region using population, employment and travel demand forecasts. Air quality modeling simulations were conducted using both current and future land cover. Meteorological modeling simulations indicate a 0.5 C increase in daily maximum air temperatures by 2030. Air quality modeling simulations show substantial differences in relative contributions of individual atmospheric pollutant constituents as a result of land cover change. Enhanced boundary layer mixing over the city tends to offset the increase in ozone concentration expected due to higher surface temperatures as a result of urbanization.

Quattrochi, Dale A.↗
DOE OSTI2024

Collaborative Research: Vlasov-Maxwell Simulations to Resolve Electron Heating and Dissipation, in Quasi-Perpendicular Shocks (Final Report)

Collisionless shocks are a grand challenge problem in plasma physics and have been the subject of study for more than six decades. Shocks are ubiquitous phenomena in the universe and are responsible for transforming high energy and momentum flows into thermal energy and energetic particles. Understanding how shocks operate is of primary importance to understand the sun-earth coupling, protecting manned missions and spacecrafts from high energy particles, inertial confinement fusion, and radiation observed from astrophysical plasmas, such as supernova remnants and astrophysical jets. A major unanswered question on this frontier is, how does a collisionless plasma transform flow energy and momentum into electron thermal energy? Many potential mechanisms have been proposed to perform the conversion between flow and thermal energy in a collisionless plasma, but the answer has been elusive. To solve the mystery, non-relativistic perpendicular and quasi-perpendicular shocks are studied via a coordinated approach employing cutting-edge numerical simulations with the continuum kinetic code Gkeyll and spacecraft observations supplied by NASA's Magnetospheric Multiscale (MMS) mission. In both sets of data, we employ novel techniques to identify how and where energy is exchanged between electromagnetic fields and plasma particles. By combining cutting-edge spacecraft data and numerical simulations with these diagnostics, we have been able to identify some of the primary mechanisms responsible electron heating and dissipation in heliospheric shocks. In addition to electron dynamics, we have complete access to proton simulation and in situ data, enabling us to characterize proton heating and acceleration in quasi-perpendicular shocks. Many astrophysical quasi-perpendicular shocks have similar parameters to those in this study, including supernova remnants and shocks in galaxy clusters. Additionally, the simulation code, Gkeyll, and associated analysis scripts are openly available for community use. This award has supported a collaborative effort between Princeton University, the University of Arizona - Tucson, and the University of Maryland - College Park. The award funded three early career scientists, including the funding and training of one female postdoctoral researcher, who was involved in all aspects of the MMS data analysis and some portions of the simulation analysis.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

When Do Different Scenarios of Future Electricity Demand Start to Meaningfully Diverge?

Climate and population change are known to influence electricity demand, but what is the impact of uncertainty in climate and population projections on electricity demand in the United States (U.S.) over the next 30 years? This question has important implications for investment decisions in the energy sector, which are typically made using a 15- to 30-year time horizon. Simply put, if future climate and population scenarios do not lead to meteorological conditions and subsequent energy demands that are distinctly different within the first 30 years then, for the purposes of investment decisions, it may not matter which potential pathway we are most likely on. The Integrated, Multisector, Multiscale Modeling (IM3) project has generated a wide, yet plausible range of 21st century high-resolution climate and population scenarios for the U.S. The IM3 projections span two climate scenarios (Representative Concentration Pathways 4.5 and 8.5) and two population scenarios (Shared Socioeconomic Pathways 3 and 5). For each of the climate scenarios, we reflect a range of climate model uncertainty by using boundary conditions from a set of climate models that are hotter and colder than the multi-model mean. In total there are eight (2 x 2 x 2) IM3 scenarios. This work explores a basic question: When do future climate and energy outcomes start to meaningfully diverge across the eight scenarios? The analysis is done on both the raw meteorology time-series from each scenario as well as a time-series of projected total electricity demand generated using IM3's Total ELectricity Loads (TELL) model. We also explore the spatial heterogeneity of the divergence signal to identify regions of the country that may be more or less path dependent.

Climate Change↗
NASA NTRS2019

Uniaxial Tensile Properties of AS4 3D Woven Composites with Four Different Resin Systems: Experimental Results & Analysis - Property Computations

As a part of the NASA Composite Technology for Exploration project, eight different AS4 3D orthogonal woven composite panels were manufactured and were subjected to mechanical testing including uniaxial tension along the weaves' warp direction. Each set, with four different resin systems (KCR-IR6070, EP2400, RTM6, and RS-50), included weave architectures designed using 12K and 6K AS4 carbon fiber yarns. For the tension testing conducted at Room Temperature Ambient (RTA) conditions, the elastic modulus and strength of these eight panels (as-processed and thermally cycled) were measured and compared while the potential evolution of micro-cracking before and after thermal cycling were monitored via optical microscopy and X-Ray Computed Tomography. The data set also included test results of the as-processed materials at Elevated Temperature Wet (ETW) conditions. In the second part of this study, efforts were made to compute elastic constants for AS4 6K/RTM6 and AS4 12K/RTM6 materials by implementing a finite element approach and the Multiscale Generalized Method of Cells (MSGMC) technique developed at NASA Glenn Research Center. Digimat-FE was used to model the weave architectures, assign properties, calculate yarn properties, create the finite element mesh, and compute the elastic properties by applying periodic boundary conditions to finite element models of each repeating unit cell. The required input data for MSGMC was generated using Matlab® from Digimat exported weave information. Experimental and computational results were compared, and the differences and limitations in correlating to the test data were briefly discussed.

Property Computations↗
NASA NTRS2019

Uniaxial Tensile Properties of AS4 3D Woven Composites with Four Different Resin Systems: Experimental Results and Analysis: Property Computations

As a part of the NASA Composite Technology for Exploration project, eight different AS4 3D orthogonal woven composite panels were manufactured and were subjected to mechanical testing including uniaxial tension along the weaves' warp direction. Each set, with four different resin systems (KCR-IR6070, EP2400, RTM6, and RS-50), included weave architectures designed using 12K and 6K AS4 carbon fiber yarns. For the tension testing conducted at Room Temperature Ambient (RTA) conditions, the elastic modulus and strength of these eight panels (as-processed and thermally-cycled) were measured and compared while the potential evolution of micro-cracking before and after thermal cycling were monitored via optical microscopy and X-Ray Computed Tomography. The data set also included test results of the as-processed materials at Elevated Temperature Wet (ETW) conditions. In the second part of this study, efforts were made to compute elastic constants for AS4 6K/RTM6 and AS4 12K/RTM6 materials by implementing a finite element approach and the Multiscale Generalized Method of Cells (MSGMC) technique developed at NASA Glenn Research Center. Digimat-FE was used to model the weave architectures, assign properties, calculate yarn properties, create the finite element mesh, and compute the elastic properties by applying periodic boundary conditions to finite element models of each repeating unit cell. The required input data for MSGMC was generated using Matlab® from Digimat exported weave information. Experimental and computational results were compared, and the differences and limitations in correlating to the test data were briefly discussed.

Property Computations↗
DOE OSTI2023

Predicting encapsulant delamination in photovoltaic modules bridging photochemical reaction kinetics and fracture mechanics

Abstract Photovoltaic (PV) modules are subjected to environmental stressors (UV exposure, temperature, and humidity) that cause degradation within the encapsulant and its interfaces with adjacent glass and cell substrates. To save experimental time and to enable long‐term assessment with intensive degradation only taking place after many years, the development of predictive models is indispensable. Previous works have modeled the delamination of the ethylene vinyl acetate (EVA) encapsulant/glass and encapsulant/cell interfaces under field aging conditions with fundamental photochemical degradation reactions that lead to molecular scission and loss of interfacial adhesion, characterized by the fracture resistance, G c . However, these models were fundamentally limited in that the following aspects were not incorporated: (i) molecular crosslinking in the field, (ii) synergistic autocatalytic interactions of degradation mechanisms, (iii) connection between degraded encapsulant structure and its mechanical properties, and (iv) rigorous treatment of the plasticity contribution to G c with finite element models. Here, we present a time‐dependent multiscale model that addresses these limitations and is applicable to a wide range of encapsulants and interfaces. For the reference EVA encapsulant and its interfaces with the glass and cell, the presented model predicts an initial rise in G c in the first 3 years of field aging from crosslinking, then a subsequent sharp decline from degradation mechanisms. We used nanoindentation to measure the changes in EVA mechanical properties over exposure time to tune the model parameters. The model predictions of G c and mechanical properties match with experimental data and show an improvement compared to previous models. The model can even predict switches in failure interfaces, such as the observed EVA/cell to EVA/glass transition. We also conducted a sensitivity analysis study by varying the degradation and crosslinking kinetic parameters to demonstrate their effects on G c . Model extensions to polyolefin elastomer‐ and silicone‐encapsulants and their interfaces are also demonstrated.

Liu, Kuan↗
DOE OSTI2026

Molecular insights into CO 2 -to-bicarbonate transformation in functionalized anion exchange ionomers for electrochemical separations

Bipolar membrane (BPM) electrochemical processes are a promising platform for carbon dioxide (CO 2 ) separations, but the molecular level thermodynamic and kinetic understanding of CO 2 -to-bicarbonate (HCO 3 − ) transformation remain poorly understood. This study employs a multiscale computational approach to systematically explore the adsorption and reactive transformation of CO 2 in five anion exchange ionomer systems. Classical molecular dynamics (MD) simulation results demonstrate that polymers with imidazolium groups significantly reduce CO 2 diffusion and enhance (OH − )–CO 2 interactions due to stronger electrostatic and π-interactions. Compared to the commonly used quaternary ammonium ionomers, imidazolium-functionalized ionomers show improved CO 2 proximity and interaction strength. Ab initio MD and density functional theory (DFT) calculations reveal that the benzyl-substituted imidazolium (IM-Ben) substantially reduces the energy barrier for HCO 3 − formation (∼72 meV lower) compared to the alkyl-substituted IM-nBu, while also mitigating imidazolium deprotonation under moderate hydration conditions. Transition state analysis shows IM-Ben forms more extensive hydrogen-bonding networks, which stabilize the transition state structure and contribute to a lower energy barrier for bicarbonate formation. These findings highlight the advantage of the adjacent benzyl moiety in enabling efficient CO 2 -to-bicarbonate transformation via hydrated hydroxide ion counterions, offering mechanistic insights and clear molecular design principles for optimizing anion exchange ionomers at bipolar membrane interfaces for electrochemical CO 2 separation applications.

Bipolar membranes, Reactive transformation of CO2,↗
DOE OSTI2023

Comparing Mapper Graphs of Artificial Neuron Activations

The mapper graph is a popular tool from topological data analysis that provides a graphical summary of point cloud data. It has been used to study data from cancer research, sports analytics, neurosciences, and machine learning. In particular, mapper graphs have been used recently to visualize the topology of high-dimensional artificial neural activations from convolutional neural networks and large language models. However, a key question that arises from using mapper graphs across applications is how to compare mapper graphs to study their structural differences. In this paper, we introduce a distance between mapper graphs using tools from optimal transport. We demonstrate the utility of such a distance by studying the topological changes of neural activations across convolutional layers in deep learning, as well as by capturing the loss of structural information for multiscale mapper.

mapper graphs, computational topology, machine lea↗
DOE OSTI2022

Multiscale Interaction of Turbulence, Temperature, and Soot Formation: Measurements for Critical Assessments of Chemical Kinetics and Mechanisms

This program targeted an improved understanding of how turbulence affects soot formation chemistry (directly and indirectly) with a particular focus on detailing the multiscale coupling between flow turbulence, mixing, thermal transport, and soot formation kinetics in gas-phase reacting systems. In this project, simultaneous, quantitative multi-dimensional velocity, soot volume fraction, and gas-phase temperature measurements in turbulent non-premixed sooting flames were developed. These new diagnostics tools can be used to elucidate the relative effects of fluid kinematics, mixing, thermal processes, and turbulence/scalar time/length scales on soot formation chemistry and topology. Simultaneous multi-parameter measurements were acquired within a series of flames with different Reynolds numbers and spatial locations to investigate the inter-dependence of soot, temperature, and turbulence within the soot inception, growth, and oxidation region. Preliminary assessment of the results has been completed at the project end and detailed analysis is planned following the completed program.

02 PETROLEUM↗