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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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
NASA NTRS2003

Estimating Terrestrial Carbon Exchange from Space: How Often and How Well?

Data from a new space mission measuring integrated light-use efficiency could provide a breakthrough in understanding of global carbon, water, and energy dynamics, and greatly improve the accuracy of model predictions for terrestrial carbon cycles and climate. Over the past decade, Gamon and others have shown that changes in photo-protective pigments are sensitive indicators of declines in light-use efficiency of plants and plant canopies. The requirements for integrated diurnal measurements from space need to be defined, before a space mission can be formulated successfully using this concept. We used towerbased CO 2 flux data as idealized proxies for remote measurements, examining their sampling properties. Thousands of half-hourly CO 2 flux measurements are needed before their average begins to converge on an average annual net CO 2 exchange. Estimates of daily integrated fluxes (i.e., diurnal curves) are more statistically efficient, especially if the spacing between measured days is quasiregular, rather than random. Using a few measurements per day one can distinguish among days with different net CO 2 exchanges. Fluxes sampled between mid-morning to mid-afternoon are more diagnostic than early morning or late afternoon measurements. Similar results (correlation >0.935) were obtained using 2 measurements per day with high accuracy ([:plusmn:]5%), 3 measurements per day with medium accuracy ([:plusmn:] 10%), or 5 measurements per day at lower accuracy ([:plusmn:]20%). An observatory in a geosynchronous or near-geosynchronous orbit could provide appropriate observations, as could a multi-satellite constellation in polar orbits, but there is a potential trade-off between the required number of observations per day and quality of each observation.

Knox, Robert G.↗
NASA NTRS1999

Interactive Sectoring and Animation of Global Change Data

In order to analyze and share results of global change data sets, scientists require a venue in which to exchange their results. One appropriate medium for these collaborative efforts is the world wide web. Intuitive and efficient user interfaces, and background processes have been developed at the Global Hydrology and Climate Center to interactively view weather satellite, radar, global temperature anomaly, and model output data using the world wide web. These tools combine scripts, Java and C code which allows the user to easily interact with data, to create high resolution sector images, and sectored animation sequences. This paper examines the architecture and interfaces and how they are used for collaborative research.

Meyer, Paul J.↗
DOE OSTI2024

Representing cropping systems with the MEMS 2 ecosystem model

Abstract Croplands have been the focus of substantial investigation due to their considerable potential for sequestering carbon. Understanding the potential for soil organic carbon (SOC) sequestration and necessary management strategies will be enabled with accurate process‐based models. Accurately representing crop growth and agricultural practices will be critical for realistic SOC modeling. The MEMS 2 model incorporates a current understanding of SOC formation and stabilization, measurable SOC pools, and deep SOC dynamics and is seen as a highly promising tool to inform management intervention for SOC sequestration. Thus far, MEMS 2 has been developed to represent grasslands. In this study, we further developed MEMS 2 to model annual grain crops and common agricultural practices, such as irrigation, fertilization, harvesting, and tillage. Using four Ameriflux sites, we demonstrated an accurate simulation of crop growth and development. Model performance was strong for simulating aboveground biomass (index of agreement [d] range of 0.89–0.98) and green leaf area index (dfrom 0.90 to 0.96) across corn, soybean, and winter wheat. Good agreement with observations was also achieved for net ecosystem CO 2 exchange (dfrom 0.90 to 0.96), evapotranspiration (dfrom 0.91 to 0.94), and soil temperature (dof 0.96), while discrepancy with the available soil water content data remain (dfrom 0.14 to 0.81 at four depths to 100 cm). While we will continue model testing and improvement, MEMS 2 (version 2.14) has now demonstrated its ability to effectively simulate the growth of common grain crops and practices.

Agriculture↗
NASA NTRS1990

Climate and smoke - An appraisal of nuclear winter

A reevaluation is presented of the 'nuclear winter' scenario of Turco et al. (1983). New pertinent data have emerged from laboratory studies, field experiments, and numerical models on the smoke-plume, mesoscale, and global scales. A full-scale nuclear exchange's probable soot injections lead, in three-dimensional climate simulations, to midsummer land temperature decreases averaging 10-20 C in northern midlatitudes, with local cooling of as much as 35 C. Anomalous circulation patterns due to solar heating of the soot could stabilize the upper atmosphere against overturning, thereby prolonging the soot's residence time in the atmosphere. Monsoon disruptions and severe ozone layer depletion are also foreseen.

Turco, R. P.↗
NASA NTRS1993

DSMC and continuum analyses of low-density nozzle flow

Two different approaches, the direct-simulation Monte Carlo (DSMC) method based on molecular gas dynamics and a finite-volume approximation of the Navier-Stokes equations, which are based on continuum gas dynamics, are employed in the analysis of a low-density gas flow in a small converging-diverging nozzle. The fluid experiences various kinds of flow regimes including continuum, slip, transition, and free-molecular. Results from the two numerical methods are compared with Rothe's experimental dam, in which density and rotational temperature variations along the centerline and at various locations inside a low density nozzle were measured by the electron-beam fluorescence technique. The continuum approach showed good agreement with the experimental data as far as density is concerned. The results from the DSMC method showed good agreement with the experimental data both in the density and the rotational temperature. It is also shown that the simulation parameters, such as the gas/surface interaction model, the energy exchange model between rotational and translational modes, and the viscosity temperature exponent, have substantial effects on the results of the DSMC method.

Chung, Chan-Hong↗
NASA NTRS1994

Low-Density Nozzle Flow by the Direct Simulation Monte Carlo and Continuum Methods

Two different approaches, the direct simulation Monte Carlo (DSMC) method based on molecular gasdynamics, and a finite-volume approximation of the Navier-Stokes equations, which are based on continuum gasdynamics, are employed in the analysis of a low-density gas flow in a small converging-diverging nozzle. The fluid experiences various kinds of flow regimes including continuum, slip, transition, and free-molecular. Results from the two numerical methods are compared with Rothe's experimental data, in which density and rotational temperature variations along the centerline and at various locations inside a low-density nozzle were measured by the electron-beam fluorescence technique. The continuum approach showed good agreement with the experimental data as far as density is concerned. The results from the DSMC method showed good agreement with the experimental data, both in the density and the rotational temperature. It is also shown that the simulation parameters, such as the gas/surface interaction model, the energy exchange model between rotational and translational modes, and the viscosity-temperature exponent, have substantial effects on the results of the DSMC method.

Chung, Chang-Hong↗
NASA NTRS2010

Orbit Determination Toolbox

The Orbit Determination Toolbox is an orbit determination (OD) analysis tool based on MATLAB and Java that provides a flexible way to do early mission analysis. The toolbox is primarily intended for advanced mission analysis such as might be performed in concept exploration, proposal, early design phase, or rapid design center environments. The emphasis is on flexibility, but it has enough fidelity to produce credible results. Insight into all flight dynamics source code is provided. MATLAB is the primary user interface and is used for piecing together measurement and dynamic models. The Java Astrodynamics Toolbox is used as an engine for things that might be slow or inefficient in MATLAB, such as high-fidelity trajectory propagation, lunar and planetary ephemeris look-ups, precession, nutation, polar motion calculations, ephemeris file parsing, and the like. The primary analysis functions are sequential filter/smoother and batch least-squares commands that incorporate Monte-Carlo data simulation, linear covariance analysis, measurement processing, and plotting capabilities at the generic level. These functions have a user interface that is based on that of the MATLAB ODE suite. To perform a specific analysis, users write MATLAB functions that implement truth and design system models. The user provides his or her models as inputs to the filter commands. The software provides a capability to publish and subscribe to a software bus that is compliant with the NASA Goddard Mission Services Evolution Center (GMSEC) standards, to exchange data with other flight dynamics tools to simplify the flight dynamics design cycle. Using the publish and subscribe approach allows for analysts in a rapid design center environment to seamlessly incorporate changes in spacecraft and mission design into navigation analysis and vice versa.

Carpenter, James R.↗
NASA NTRSDate not supplied

NASA’s Prototype Spectral Water Inversion Processor and Emulator (SWIPE): Towards Global Coastal and Inland Water Quality and Algal Biodiversity Monitoring

Degradation of Earth’s inland water resources due to anthropogenic perturbations and climate anomalies at both local and global scales continues to place human health at substantial risk. There is now a growing necessity to develop pragmatic approaches that allow timely and effective extrapolation of local processes, to spatially resolved global products, and to promote operational and sustainable resource policy management. This presentation will provide updates on NASA’s prototype open-source aquatic modeling platform, Spectral Water Inversion Processor and Emulator (SWIPE), which is a comprehensive, multi-faceted modeling platform for both forward and inverse modeling of diverse aquatic ecosystems from the benthos to top-of-atmosphere (TOA). SWIPE provides a cohesive application which leverages recent advancements in particle modeling, Big Data analytics, and machine learning to develop a high-fidelity synthetic training ground for sensitivity studies and algorithm development for multispectral or upcoming hyperspectral missions. Some of the prominent features of SWIPE to be discussed include: 1. Advanced hyperspectral modeling of globally diverse algal and non-algal particles using a novel two-layer coated sphere scattering model and radiative transfer modeling, 2. Massive, highly detailed synthetic spectral libraries of Analysis-Ready-Data (ARD) which include spectral libraries of particle microphysics, water biogeophysical and optical properties, as well as surface and TOA reflectances at 1 nm resolution, 3. An ensemble of pre-built analytic, machine learning, and deep learning inversion algorithms for various water quality and biodiversity related retrieval parameters and uncertainty quantification, 4. Sensor-agnostic water quality inversion at wide ranging spatial and spectral resolutions including a codebase for seamless application in the Google Earth Engine and NASA Earth Exchange (NEX) for planetary scale analysis. SWIPE will be a fully open-source platform based in python with comprehensive documentation, tutorials, and options for distributed computing on high performance computing clusters or on single, local machines. Further, we will discuss how we envision SWIPE contributing towards a global analysis of coastal and inland water quality dynamics.

top-of-atmosphere (TOA)↗
DOE OSTI2025

Phase-field modeling of diffusion bonding in 316H stainless steel: Impact of processing conditions on grain morphology and bonding quality

A novel multi-phase, multi-component phase‐field model is presented to study the diffusion bonding of 316H stainless steel. Combined with targeted experimental investigations, this model simulates the bond-growth process and predicts the bonding quality. Unlike previous models, our approach captures the simultaneous evolution of voids and grain structures, while quantifying bonding quality using defined bonding ratio. A comprehensive analysis of bond process control is performed by changing temperature, pressure and surface roughness observing the resulting bond structure, which is consistent with experimental observations and analytical predictions. Temperature is determined to be the dominant factor, with the transition from a flat to a robust bond occurring between 1000 °C and 1050 °C. At the ideal bonding temperature of 1050 °C, a surface roughness exceeding 0.6 μm or an applied stress below 4 MPa results in poor bonding quality. Beyond this, higher pressures and smoother surfaces reduce void size, accelerate void shrinkage, and lead to improved bond integrity. This diffuse-interface model can be extended to other material systems if supplied with appropriate thermodynamic and kinetic data. In conclusion, this makes it an effective modeling platform for optimizing high-temperature diffusion bonding and developing reliable bonded components such as compact heat exchangers.

Diffusion bonding↗
DOE OSTI2025

Spin dynamics in the itinerant antiferromagnet SrCr 2 ⁢As 2

SrCr 2 ⁢As 2 is an itinerant antiferromagnet in the same structural family as the SrFe 2 ⁢As 2 high-temperature superconductors. Here, we report our calculations of exchange-coupling parameters 𝐽 𝑖⁢𝑗 for SrCr 2 ⁢As 2 using a static linear-response method based on first-principles electronic-structure calculations. We find that the dominant nearest-neighbor exchange coupling 𝐽 1 >0 is antiferromagnetic whereas the next-nearest-neighbor exchange coupling 𝐽 2 <0 is ferromagnetic with 𝐽 2 /𝐽 1 = −0.68, reinforcing the checkerboard in-plane magnetic structure. Thus, unlike other transition-metal arsenides based on Mn, Fe, or Co, we find no competing magnetic interactions in SrCr 2 ⁢As 2 , which aligns with experimental findings. Moreover, the orbital resolution of exchange interactions shows that 𝐽 1 and 𝐽 2 are dominated by direct exchange mediated by the Cr 𝑑 orbitals. To validate the calculations we conduct inelastic neutron-scattering measurements on powder samples that show steeply dispersive magnetic excitations arising from the magnetic Γ points and persisting up to energies of at least 175 meV. The spin-wave spectra are then modeled using the Heisenberg Hamiltonian with the theoretically calculated exchange couplings. In conclusion, the calculated neutron-scattering spectra are in good agreement with the experimental data.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Deep Reinforcement Learning for Distribution System Operations: A Tutorial and Survey

Here, the rapid evolution of modern electric power distribution systems into complex networks of interconnected active devices, distributed generation (DG), and storage poses increasing difficulties for system operators. The large-scale integration of distributed energy resources (DERs) and the rapid exchange of measurement data via communication networks present major opportunities for advancing grid operations but also introduce greater uncertainty, higher data dimensionality, more complex network and device models, and challenging control and optimization problems. Deep reinforcement learning (DRL) algorithms are promising in addressing these challenges. However, they have not been effectively adapted for power systems applications, requiring extensive customization for implementation and evaluation. This has resulted in reproducibility challenges and a steep learning curve for researchers new to applying DRL algorithms to the power systems domain. To bridge these gaps, this tutorial aims to serve as a valuable resource for researchers interested in exploring learning-based algorithms to operate active power distribution networks. Specifically, this work presents a generalized process for translating sequential decision-making problems in power distribution systems into Markov decision process (MDP) formulations, illustrated through concrete grid service examples. Additionally, we introduce a simple environment design strategy to develop and evaluate example DRL algorithms for distribution system applications, complete with an included code repository to guide users through environment construction.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1992

Tests characterizing bioprocessor hardware for analytical modeling

The tests outlined in this paper were used to characterize the hardware components of the Salad Machine, a small NASA-developed bioprocessor. The data from these tests are presented, and the methods by which this data can be integrated into system mathematical models are briefly discussed. The subsystems and physical processes discussed include the lighting system, the air loop (condensing heat exchanger and the blower), heat transfer to the surroundings, and leakage. Through this effort it was learned that in the development of a test protocol, care should be taken to order the tests such that environmental parameters, particularly humidity, require as few large adjustments as possible. Sensor calibration and installation take a substantial amount of time, which should be built into the test schedule. Two properties were particularly hard to quantify: the air flow rate and the energy from the lighting system entering into the growth volume. Flow rate can be measured using the appropriate device for the system configuration and airflow. Lighting system radiation level was measured using three methods. The results of these methods varied substantially, putting off conclusive quantification of this value.

Gustavino, S.↗
NASA NTRS2019

Solar Activity Modeling: From Subgranular Dynamical Scales to the Solar Cycles

The dynamical effects of solar magnetoconvection span a wide range spatial and temporal scales that extend from the interior to the corona and from fast turbulent motions to global magnetic activity. To study the solar activity on short temporal scales (from minutes to hours), we use 3D radiative MHD simulations that allow us to investigate complex turbulent interactions that drive various phenomena, such as plasma eruptions, spontaneous formation of magnetic structures, funnel-like structures and magnetic loops in the corona, and others. In particular, we focus on multi-scale processes of energy exchange across layers of the solar interior and atmosphere, which contribute to coronal heating and eruptive dynamics. For modeling global-scale activity, we use a data assimilation approach that has demonstrated great potential for building reliable long-term forecasts of solar activity. In particular, it has been shown that the Ensemble Kalman Filter (EnKF) method applied to the Parker-Kleeorin-Ruzmakin dynamo model is capable of predicting solar activity up to one sunspot cycle ahead in time, as well as estimating the properties of the next cycle a few years before it begins. In this presentation, using the available magnetogram data, we discuss development of the methodology and forecast quality criteria (including forecast uncertainties and sources of errors). We demonstrate the influence of observational limitations on prediction accuracy, and we present the EnKF predictions of the upcoming Solar Cycle (25) based on both the sunspot number series and observed magnetic fields and discuss the uncertainties and potential of the data assimilation approach for modeling and forecasting solar activity.

Kitiashvili, I. N.↗
NASA NTRSDate not supplied

Integrated Bosch Process System Models for In-Situ Oxygen and Carbon Production

In-Situ Resource Utilization (ISRU) technology is a vital component to NASA’s mission of a sustainable presence on the Moon and Mars. Local resources can be leveraged to reduce resupply frequency and mass. Elements of the Bosch process, combined with the carbothermal reduction process, can produce oxygen on the lunar surface with minimal consumables. The Bosch process can also produce oxygen on the Martian surface by using the CO 2 -rich environment. Between both systems, adsorption pump, solar thermal energy, carbon formation reactor, and water recovery subsystems are modeled and integrated to create a functional model in MATLAB software. The model is used to simulate performance of the system and reduce mass, power, and volume requirements. This integrated system model provides a tool to scale ISRU technologies for oxygen and carbon production. The MATLAB model is created by developing a system of independent subsystem models that are solved for their quasi-steady state values which can be integrated with respect to time to determine the change in current states. A flexible time stepping method is used to ensure a high level of accuracy during periods of rapid change while still making use of a simple explicit integration method. The flexible time step is calculated for each independent subsystem and the minimum value from those is used as the overall time step. A flexible time step is calculated by dividing a resolution value, or the maximum change per time step, by the variables current rate of change. The maximum value from all points in space is used for subsystem models that contain multiple values. The process is done for every variable that is being monitored in each subsystem and the global minimum is used as that iteration’s timestep. Several assumptions used in the MATLAB model for fluid flow dynamics, such as 1-D gas flow through the sorption pump, are supported by modeling in Ansys Fluent software. The Lunar oxygen production system is outlined in Fig. 1. The carbothermal reduction subsystem uses solar energy to heat a mixture of lunar regolith and carbon powder to produce carbon monoxide. To begin, the carbon monoxide feeds to the modified Bosch subsystem along with hydrogen gas. The reactants then enter the carbon formation reactor where water and carbon powder are produced. Solar thermal energy is used to add energy to the reactor, but waste heat from the carbothermal process is another potential heat source. The water is collected and electrolyzed to produce hydrogen which reenters the Bosch subsystem, and the oxygen is stored for downstream use. The carbon powder is collected and feeds back into the carbothermal subsystem. The Martian oxygen production system uses the full Bosch process and is outlined in Fig 2. A CO 2 adsorption pump thermally cycles to scrub and pressurize CO 2 from the environment. Along with an initial supply of hydrogen, the reactants enter the Reverse Water Gas Shift Reactor (RWGSR) which produces carbon monoxide and water. Carbon monoxide and unreacted hydrogen enter the carbon formation reactor to produce water and carbon powder. The water is collected from both reactors and electrolyzed to reintroduce hydrogen and store oxygen for propellant production or life support. Carbon is removed from the carbon formation reactor and stored. The adsorption pump utilizes rapid cycle temperature swings within a stack of zeolite coated surfaces. The subsystem model solves 1-D quasi-steady conservation laws of the quasi-steady form, shown in Eq. 1, for the gas stream and heat exchange liquid to predict performance parameters such as breakthrough capacity and optimum cycle time. The source term S is used to capture interactions between the fluid flows and the sorbent. A quasi-steady-state scheme is used where no time derivatives appear in the governing equations, except for those in the source terms. This results in an autonomous system, where ∂F/∂x = ƒ(F). The fluxes F are provided at the inlet, and an explicit method is used to solve for the spatial distribution of F. The heat and mass flows to the sorbent are then extracted from the source terms. These flows are numerically integrated to produce a 1-D solution for the system’s state as a function of both time and space. The body of the adsorption pump is separated into two semi-independent models: the heat exchanger fluid flow and gas flow through the zeolite coated surfaces. Both models are solved using the above-described method to find a 1-D solution as a function of space and interact only once a timestep is taken. The interaction point is the sorbent through which all heat transfer between the two models must occur. Sorbent mass adsorption is calculated using the Lagergren model, shown in Eq. 2, where the transfer coefficient, λ D , is found by solving a system of nondimensionalized equations derived by using the heat and mass transfer analogy for transport phenomena. Using Grade 544 Type 13X zeolite as the sorbent material, the equilibrium concentration, θ eq , is calculated using the k-site Langmuir isotherm and fit parameters. Additionally, the enthalpy of adsorption used in the model is computed by interpolation of available data [1]. The subsystem model was validated using the Rapid Cycle Temperature Swing Adsorption (RC-TSA) pump. The solar thermal energy subsystem focuses on a solar concentrator concept with a heat exchanger to heat the reactants before entering the carbon formation reactor. The subsystem model assumes a fixed solar flux and reflector efficiency to calculate the reactant temperature given the incoming temperature, pressure, and exchanger geometry. The receiver is a custom manufactured series of copper blocks with serpentine channels to increase its surface area and the residence time of the reactants to heat up to 550 °C. The subsystem model was validated using a heat exchanger developed at NASA Glenn Research Center (GRC). The solar thermal energy subsystem focuses on a solar concentrator concept with a heat exchanger to heat the reactants before entering the carbon formation reactor. The subsystem model assumes a fixed solar flux and reflector efficiency to calculate the reactant temperature given the incoming temperature, pressure, and exchanger geometry. The receiver is a custom manufactured series of copper blocks with serpentine channels to increase its surface area and the residence time of the reactants to heat up to 550 °C. The subsystem model was validated using a heat exchanger developed at NASA Glenn Research Center (GRC).

In situ Resource Utilization↗
NASA NTRS1994

An Approach to Estimating Surface Parameters and Fluxes Using Modeling and Multispectral Remote Sensing

Water and energy exchanges at the land-atmosphere interface play a key role in determining patterns of regional and global climate. However, accurate estimation of surface fluxes of sensible and latent over arid and semiarid regions is a challenging task. In this study, a scenario for assimilating satellite data in the visible-infrared (AVHRR) and in the microwave (SSM/I) spectral ranges in a hydrological flux model will be presented. The aim of our investigation over the HAPEX-Sahel area in West Africa is to show that the use of multispectral remotely sensed data, in conjunction with radiative transfer models and hydrological flux model, can provide reasonable estimates of the surface fluxes. A discussion of the potentials and limitations of the approach is presented.

surface fluxes climate satellite data↗
NASA NTRS2012

Architecting the Human Space Flight Program with Systems Modeling Language (SysML)

The next generation of missions in NASA's Human Space Flight program focuses on the development and deployment of highly complex systems (e.g., Orion Multi-Purpose Crew Vehicle, Space Launch System, 21st Century Ground System) that will enable astronauts to venture beyond low Earth orbit and explore the moon, near-Earth asteroids, and beyond. Architecting these highly complex system-of-systems requires formal systems engineering techniques for managing the evolution of the technical features in the information exchange domain (e.g., data exchanges, communication networks, ground software) and also, formal correlation of the technical architecture to stakeholders' programmatic concerns (e.g., budget, schedule, risk) and design development (e.g., assumptions, constraints, trades, tracking of unknowns). This paper will describe how the authors have applied System Modeling Language (SysML) to implement model-based systems engineering for managing the description of the End-to-End Information System (EEIS) architecture and associated development activities and ultimately enables stakeholders to understand, reason, and answer questions about the EEIS under design for proposed lunar Exploration Missions 1 and 2 (EM-1 and EM-2).

scheduling↗
DOE OSTI2026

Model-based economic analysis under uncertainty for PFAS treatment by granular activated carbon and ion exchange technologies

Recent drinking water regulations have imposed the need for per- and polyfluoroalkyl substances (PFAS) remediation. In response, treatment facilities may be required to retrofit existing treatment schemes to treat PFAS below maximum contaminant levels (MCLs). Adsorption technologies such as granular activated carbon (GAC) and ion exchange (IX) have been demonstrated to be effective; however, there are limited techno-economic metrics available which provide guidance on technology selection and design for diverse PFAS-containing source water conditions. Process systems engineering (PSE) tools which can traditionally perform these analyses are hindered by the data availability, model validity, and understanding of treatment phenomena for emerging contaminants. This work employs published data regressions, statistical models, process models, techno-economic analyses, and other process systems tools in a model-based uncertainty framework to consider the limitations of emerging contaminant research. Through this analysis framework, economic results are provided as probabilistic distributions based on the uncertainty of the models and diverse conditions that treatment facilities experience.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Measurements and kinetic modeling of O 2 vibrational kinetics in O 2 –Ar mixtures partially dissociated by a Ns pulse discharge

Vibrational kinetics of O 2 is studied during the O atom recombination in an O 2 –Ar mixture, partially dissociated by a burst of ns discharge pulses in a heated plasma flow reactor. The time-resolved temperature in the discharge afterglow is determined by Rayleigh scattering. Time-resolved O atom number density is measured by ps Two-Photon absorption Laser Induced Fluorescence, calibrated in xenon. Time-resolved vibrational level populations of molecular oxygen, O 2 (v= 8–20), are measured by ps Laser Induced Fluorescence (LIF), with the absolute calibration by NO LIF. Time-resolved ozone number density is monitored by broadband UV absorption. The results are compared with the predictions of a state-specific kinetic model. The experimental data indicate a rapid initial decay of O 2 (v) populations generated by electron impact in the discharge, due to the vibration-translation (V–T) relaxation by O atoms. This is followed by a slower population reduction, on the time scale much longer compared to that for V–T relaxation or vibration-vibration (V–V) exchange. Both O atoms and the O 2 (v) populations decay on the same time scale, indicating that chemical reactions initiated by the O atom recombination result in the generation of vibrationally excited O 2 molecules. These trends are reproduced by the kinetic model, which shows that the reaction of O atoms with ozone is the dominant pathway of O 2 (v) generation at the present conditions. The predicted relative O 2 (v) populations are close to the experimental results, but absolute number densities differ from the experimental data. This is likely due to uncertainties in the absolute calibration of LIF measurements and in the spectroscopic model used in the data reduction. The present work demonstrates the capability for the absolute, time-resolved measurements of vibrationally excited O 2 in recombining gas flows, to quantify the energy partition in the recombination reactions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗