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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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Strong Thermoset Regolith UV-Curable Composite Technology (STRUCT) Overview

Future lunar surface missions require construction materials that can be manufactured in situ using lo-cal resources while operating under extreme environmental conditions. Many Lunar material demands can be solved solely with regolith by compacting or sintering. And yet past Lunar missions rely on polymeric materials, and sustained Lunar missions must reduce Earth-supplied polymers dependence. Dual-cure (Ultraviolet (UV) and thermal) polymer-regolith composites offer a promising pathway by leveraging solar UV radiation, moderate thermal in-put, and regolith. Mission mass limits, power availability and energy constraints on the lunar surface further motivate low-energy processing and curing strategies for surface construction materials. The Strong Thermoset Regolith UV-Curable Composite Technology (STRUCT) project has successfully synthesized and demonstrated dual-cure photopolymer resins derivable from in-situ resources [3]. Morphological, thermal, and mechanical characterization show that the newly formulated UV curable resin systems integrates well with lunar regolith simulants. Processing and chemistry changes, and computational analysis advanced the composite design. X-ray CT scanned and computational analysis demonstrate that resin, regolith and additives are well incorporated. The large fraction of regolith, 95% by mass, large char yield (82% mass), low thermal conductivity (0.26 W/m/K), confirm this material as a promising high-performance thermal and structural material.

thermal conductivity↗

NASA NTRS1993

Development of global/chemistry model for jet-fuel thermal stability based on observations from static and flowing experiments

Two global-chemistry models for oxidative deposition of jet fuels are evaluated by integrating them into a Computational Fluid Dynamics with Chemistry (CFDC) code. A previously developed two-step global-chemistry model was found to be insufficient to describe the thermal-oxidation and -deposition rates associated with a Jet-A fuel. A new global-chemistry model has been developed systematically based on observations from flowing and static experiments. The global-autoxidation reaction is modified such that the reaction rate becomes zeroth-order with respect to the dissolved oxygen concentration. The generation of deposit-forming precursor is coupled with the autoxidation reaction by introducing a radical species ROO. A formulation for the sticking probability has also been developed. Deposition profiles are well represented by this new model under a variety of temperature and flow conditions. The model correctly predicts the changes in magnitude and spatial location of the deposition peak due to changes in flow. The CFDC model, which is designed for flowing systems, has been extended to static experiments. The model incorporates a non-depleting species F(sub s) representing all non-oxygen compounds responsible for deposition. Static experiments were found to provide a useful and inexpensive method for estimating the concentration of F(sub s) in the fuel.

V. R. Katta↗

NASA NTRS2010

Ablation, Thermal Response, and Chemistry Program for Analysis of Thermal Protection Systems

In previous work, the authors documented the Multicomponent Ablation Thermochemistry (MAT) and Fully Implicit Ablation and Thermal response (FIAT) programs. In this work, key features from MAT and FIAT were combined to create the new Fully Implicit Ablation, Thermal response, and Chemistry (FIATC) program. FIATC is fully compatible with FIAT (version 2.5) but has expanded capabilities to compute the multispecies surface chemistry and ablation rate as part of the surface energy balance. This new methodology eliminates B' tables, provides blown species fractions as a function of time, and enables calculations that would otherwise be impractical (e.g. 4+ dimensional tables) such as pyrolysis and ablation with kinetic rates or unequal diffusion coefficients. Equations and solution procedures are presented, then representative calculations of equilibrium and finite-rate ablation in flight and ground-test environments are discussed.

Milos, Frank S.↗

NASA NTRS1997

Studies of Flame Structure in Microgravity

The present research endeavor is concerned with gaining fundamental understanding of the configuration, structure, and dynamics of laminar premixed and diffusion flames under conditions of negligible effects of gravity. Of particular interest is the potential to establish and hence study the properties of spherically- and cylindrically-symmetric flames and their response to external forces not related to gravity. For example, in an earlier experimental study of the burner-stabilized cylindrical premixed flames, the possibility of flame stabilization through flow divergence was established, while the resulting one-dimensional, adiabatic, stretchless flame also allowed an accurate means of determining the laminar flame speeds of combustible mixtures. We have recently extended our studies of the flame structure in microgravity along the following directions: (1) Analysis of the dynamics of spherical premixed flames; (2) Analysis of the spreading of cylindrical diffusion flames; (3) Experimental observation of an interesting dual luminous zone structure of a steady-state, microbuoyancy, spherical diffusion flame of air burning in a hydrogen/methane mixture environment, and its subsequent quantification through computational simulation with detailed chemistry and transport; (4) Experimental quantification of the unsteady growth of a spherical diffusion flame; and (5) Computational simulation of stretched, diffusionally-imbalanced premixed flames near and beyond the conventional limits of flammability, and the substantiation of the concept of extended limits of flammability. Motivation and results of these investigations are individually discussed.

Law, C. K.↗

NASA NTRS1990

Flux-split algorithms for flows with non-equilibrium chemistry and vibrational relaxation

The present consideration of numerical computation methods for gas flows with nonequilibrium chemistry thermodynamics gives attention to an equilibrium model, a general nonequilibrium model, and a simplified model based on vibrational relaxation. Flux-splitting procedures are developed for the fully-coupled inviscid equations encompassing fluid dynamics and both chemical and internal energy-relaxation processes. A fully coupled and implicit large-block structure is presented which embodies novel forms of flux-vector split and flux-difference split algorithms valid for nonequilibrium flow; illustrative high-temperature shock tube and nozzle flow examples are given.

Grossman, B.↗

NASA NTRS1997

Computational Modeling as a Design Tool in Microelectronics Manufacturing

Plans to introduce pilot lines or fabs for 300 mm processing are in progress. The IC technology is simultaneously moving towards 0.25/0.18 micron. The convergence of these two trends places unprecedented stringent demands on processes and equipments. More than ever, computational modeling is called upon to play a complementary role in equipment and process design. The pace in hardware/process development needs a matching pace in software development: an aggressive move towards developing "virtual reactors" is desirable and essential to reduce design cycle and costs. This goal has three elements: reactor scale model, feature level model, and database of physical/chemical properties. With these elements coupled, the complete model should function as a design aid in a CAD environment. This talk would aim at the description of various elements. At the reactor level, continuum, DSMC(or particle) and hybrid models will be discussed and compared using examples of plasma and thermal process simulations. In microtopography evolution, approaches such as level set methods compete with conventional geometric models. Regardless of the approach, the reliance on empricism is to be eliminated through coupling to reactor model and computational surface science. This coupling poses challenging issues of orders of magnitude variation in length and time scales. Finally, database development has fallen behind; current situation is rapidly aggravated by the ever newer chemistries emerging to meet process metrics. The virtual reactor would be a useless concept without an accompanying reliable database that consists of: thermal reaction pathways and rate constants, electron-molecule cross sections, thermochemical properties, transport properties, and finally, surface data on the interaction of radicals, atoms and ions with various surfaces. Large scale computational chemistry efforts are critical as experiments alone cannot meet database needs due to the difficulties associated with such controlled experiments and costs.

Meyyappan, Meyya↗

NASA NTRS1986

Numerical simulation of hypersonic, axisymmetric flowfields

Flow conditions corresponding to those of three previously conducted hypersonic axisymmetric flow experiments are presently treated by numerical solutions of the axisymmetric, thin layer Navier-Stokes equations with the Chemistry and Gasdynamic Implicit computer code's Version 2. While simulation and experimental results agree for ideal gas flows, the simulation for the case of a real gas flow reveals that the particular coupling of the gasdynamics and the chemistry used in the code degrades the convergence level obtainable, by comparison with ideal gas cases. The computed stagnation point heating is 60 percent lower than for the experiment.

Green, M. J.↗

NASA NTRS1987

Chemistry-split techniques for viscous reactive blunt body flow computations

The weak-coupling structure between the fluid and species equations has been exploited and resulted in three, closely related, time-iterative implicit techniques. While the primitive variables are solved in two separated groups and each by an Alternating Direction Implicit (ADI) factorization scheme, the rate-species Jacobian can be treated in either full or diagonal matrix form, or simply ignored. The latter two versions render the split technique to solving for species as scalar rather than vector variables. The solution is completed at the end of each iteration after determining temperature and pressure from the flow density, energy and species concentrations. Numerical experimentation has shown that the split scalar technique, using partial rate Jacobian, yields the best overall stability and consistency. Satisfactory viscous solutions were obtained for an ellipsoidal body of axis ratio 3:1 at Mach 35 and an angle of attack of 20 degrees.

Li, C. P.↗

NASA NTRS1995

Atmospheric environmental implications of propulsion systems

Three independent studies have been conducted for assessing the impact of rocket launches on the earth's environment. These studies have addressed issues of acid rain in the troposphere, ozone depletion in the stratosphere, toxicity of chemical rocket exhaust products, and the potential impact on global warming from carbon dioxide emissions from rocket launches. Local, regional, and global impact assessments were examined and compared with both natural sources and anthropogenic sources of known atmospheric pollutants with the following conclusions: (1) Neither solid nor liquid rocket launches have a significant impact on the earth's global environment, and there is no real significant difference between the two. (2) Regional and local atmospheric impacts are more significant than global impacts, but quickly return to normal background conditions within a few hours after launch. And (3) vastly increased space launch activities equivalent to 50 U.S. Space Shuttles or 50 Russian Energia launches per year would not significantly impact these conclusions. However, these assessments, for the most part, are based upon homogeneous gas phase chemistry analysis; heterogeneous chemistry from exhaust particulates, such as aluminum oxide, ice contrails, soot, etc., and the influence of plume temperature and afterburning of fuel-rich exhaust products, need to be further addressed. It was the consensus of these studies that computer modeling of interactive plume chemistry with the atmosphere needs to be improved and computer models need to be verified with experimental data. Rocket exhaust plume chemistry can be modified with propellant reformulation and changes in operating conditions, but, based upon the current state of knowledge, it does not appear that significant environmental improvements from propellant formulation changes can be made or are warranted. Flight safety, reliability, and cost improvements are paramount for any new rocket system, and these important aspects cannot be compromised. A detailed environmental cost-benefit-risk analysis must be conducted before any new chemistry or changes in rocket operating conditions should be seriously considered for any future space or defense applications. This paper presents a summary of the results of environmental assessments contained in these independent studies.

Mcdonald, Allan J.↗

NASA NTRS2019

Atmospheric Chemistry Modeling Using Machine Learning

Atmospheric chemistry models are a central tool to study the impact of chemical constituents on the environment, vegetation and human health. These models split the atmosphere in a large number of grid-boxes and consider the emission of compounds into these boxes and their subsequent transport, deposition, and chemical processing. The chemistry is represented through a series of simultaneous ordinary differential equations, one for each compound. Given the difference in life-times between the chemical compounds (milli-seconds for O1D to years for CH4) these equations are numerically stiff and solving them consists of a significant fraction of the computational burden of a chemistry model. We have investigated a machine learning approach to emulate the chemistry instead of solving the differential equations numerically. From a one-month simulation of the GEOS-Chem model we have produced a training dataset consisting of the concentration of compounds before and after the differential equations are solved, together with some key physical parameters for every grid-box and time-step. From this dataset we have trained a machine learning algorithm (regression forest) to be able to predict the concentration of the compounds after the integration step based on the concentrations and physical state at the beginning of the time step. We have then included this algorithm back into the GEOS-Chem model, bypassing the need to integrate the chemistry. This machine learning approach shows many of the characteristics of the full simulation and has the potential to be substantially faster. There are a wide range of application for such an approach - generating boundary conditions, for use in air quality forecasts, chemical data assimilation systems, etc. We discuss speed and accuracy of our approach, and highlight some potential future directions for improving it.

Keller, Christoph A.↗

NASA NTRS2019

Atmospheric Chemistry Modeling and Air Quality Forecasting Using Machine Learning

Atmospheric chemistry models are a central tool to study the impact of chemical constituents on the environment, vegetation and human health. These models split the atmosphere in a large number of grid-boxes and consider the emission of compounds into these boxes and their subsequent transport, deposition, and chemical processing. The chemistry is represented through a series of simultaneous ordinary differential equations, one for each compound. Given the difference in life-times between the chemical compounds (milli-seconds for O1D to years for CH4) these equations are numerically stiff and solving them consists of a significant fraction of the computational burden of a chemistry model.We have investigated a machine learning approach to emulate the chemistry instead of solving the differential equations numerically. From a one-month simulation of the GEOS-Chem model we have produced a training dataset consisting of the concentration of compounds before and after the differential equations are solved, together with some key physical parameters for every grid-box and time-step. From this dataset we have trained a machine learning algorithm (regression forest) to be able to predict the concentration of the compounds after the integration step based on the concentrations and physical state at the beginning of the time step. We have then included this algorithm back into the GEOS-Chem model, bypassing the need to integrate the chemistry.This machine learning approach shows many of the characteristics of the full simulation and has the potential to be substantially faster. There are a wide range of application for such an approach - generating boundary conditions, for use in air quality forecasts, chemical data assimilation systems, etc. We discuss speed and accuracy of our approach, and highlight some potential future directions for improving it.

Keller, Christoph A.↗

NASA NTRS2019

Machine Learning Application to Atmospheric Chemistry Modeling

Atmospheric chemistry models are a central tool to study the impact of chemical constituents on the environment, vegetation and human health. These models split the atmosphere in a large number of grid-boxes and consider the emission of compounds into these boxes and their subsequent transport, deposition, and chemical processing. The chemistry is represented through a series of simultaneous ordinary differential equations, one for each compound. Given the difference in life-times between the chemical compounds (milli-seconds for O (sup 1) D (Deuterium) to years for CH4) these equations are numerically stiff and solving them consists of a significant fraction of the computational burden of a chemistry model. We have investigated a machine learning approach to emulate the chemistry instead of solving the differential equations numerically. From a one-month simulation of the GEOS-Chem model we have produced a training dataset consisting of the concentration of compounds before and after the differential equations are solved, together with some key physical parameters for every grid-box and time-step. From this dataset we have trained a machine learning algorithm (regression forest) to be able to predict the concentration of the compounds after the integration step based on the concentrations and physical state at the beginning of the time step. We have then included this algorithm back into the GEOS-Chem model, bypassing the need to integrate the chemistry. This machine learning approach shows many of the characteristics of the full simulation and has the potential to be substantially faster. There are a wide range of application for such an approach - generating boundary conditions, for use in air quality forecasts, chemical data assimilation systems, etc. We discuss speed and accuracy of our approach, and highlight some potential future directions for improving it.

Keller, Christoph A.↗

NASA NTRS2023

Assessment of the Fluid Dynamics Boundary Condition in Ablating or Blowing Flows

Improved models of ablative thermal protection systems have enabled the treatment of materials and fluid behavior in a coupled manner. This paper reports a new approach to modeling the interface between fluid and material, with attention to the conservation of species mass flux and energy on the fluid side of the interface. The general equation is presented and is shown to recover the traditional uncoupled fluid/materials response interface. Including the chemical reaction terms on the CFD side of the interface makes the heat flux exchange independent of the thermodynamic reference state and, therefore, a measurable quantity. Doing so allows the material response solver to take as input the surface heat flux rather than a film coefficient. Removing the film coefficient approximation enables more direct solution of vehicle thermal response but requires consistency in the wall state. The mixing of the shock layer and pyrolysis gas is then computed with finite rate chemistry within the fluid solver. The boundary conditions described have been implemented in the DPLR v4.05.1 code. Char removal is captured using finite rate chemistry in DPLR’s gas surface interaction module. Aspects of coupling these solutions to material response are discussed.

Ablation↗

NASA NTRS2023

Assessment of the Fluid Dynamics Boundary Condition in Ablating or Blowing Flows

Ablation↗

NASA NTRS1976

The lower ionosphere of Titan

Ionization of the atmosphere of Titan by galactic cosmic rays is a very significant process throughout the altitude range from 100 to 400 km. An approximate form of the Boltzmann equation for cosmic-ray transport has been used to obtain local ionization rates. Models of both ion and neutral chemistry have been employed to compute electron and ion density profiles for three different values of the H2/CH4 abundance ratio. The peak electron density is of the order of 1000 per cu cm. The most abundant positive ions are C2/H9(+) and C3H9(+), while the predicted densities of the negative ions H(-) and CH3(-) are very small (less than one ten-thousandth that of the positive ions). It is suggested that inclusion of the ion chemistry is important in the computation of the H and CH3 density profiles in the lower ionosphere.

Capone, L. A.↗

NASA NTRS1983

Calculation of inviscid flow over shuttle-like vehicles at high angles of attack and comparisons with experimental data

A computer code HALIS, designed to compute the three dimensional flow about shuttle like configurations at angles of attack greater than 25 deg, is described. Results from HALIS are compared where possible with an existing flow field code; such comparisons show excellent agreement. Also, HALIS results are compared with experimental pressure distributions on shuttle models over a wide range of angle of attack. These comparisons are excellent. It is demonstrated that the HALIS code can incorporate equilibrium air chemistry in flow field computations.

Weilmuenster, K. J.↗

NASA NTRS1992

A High Angle of Attack Inviscid Shuttle Orbiter Computation

An accurate description of the aerothermal environment is required to minimize the weight of the Thermal Protection System required on the leeside of winged reentry vehicles. The inability of ground-test facilities to reproduce the high enthalpy, separated flow present during reentry flight conditions, coupled with the prohibitive expense of flight tests, leads to the use of an analytical method - namely Computational Fluid Dynamics (CFD) - to describe the flow. While the ultimate goal of this work is to accurately predict the leeside flow and its associated thermal environment, an essential and reasonable first step towards that goal is a comparison of pressure predictions by a code with wind-tunnel data. Until such CFD pressure predictions agree with wind-tunnel test cases, there is little hope of accurately predicting the thermal environment at flight conditions. Thus, the objective of this study is to compare the pressure distributions predicted by inviscid, perfect gas CFD to Shuttle Orbiter wind-tunnel data and to address any significant issues encountered during the computation. While flight data is available for the Shuttle Orbiter, a wind-tunnel case is chosen for this study to allow a tractable problem for preliminary investigation. A wind-tunnel case allows the perfect gas assumption for the flow chemistry. This provides a significant computational savings over a several species finite-rate chemistry model which would be necessary if high-temperature effects present at flight conditions were to be included. In addition, by concentrating on the surface pressures, the analysis need only consider inviscid flow for general evaluation of the code capability. This further reduces the computational expense due to the absence of viscous terms and the associated decrease in the number of points required for the computational grid. Previous computational efforts (such as STEIN and HALIS) have been directed toward the windward surface quantities, primarily due to restrictions in treating either the winged geometry or its associated subsonic regions at high angle of attack. The code used for this study, the LAURA (Langley Aerothermodynamic Upwind Relaxation Algorithm) code of Gnoffo, represents a state-of-the-art code for computing the flow over complex configurations at hypersonic speeds. In the study, the LAURA code is applied to a wind-tunnel condition to initiate the assessment of the code's ability to predict the flow over a relatively complex hypersonic vehicle at high angles of attack. This presentation is used to highlight the pertinent results of a more detailed investigation of the inviscid calculation over the Shuttle Orbiter with the LAURA code.

William L. Kleb↗

NASA NTRS1987

Duct flow nonuniformities for Space Shuttle Main Engine (SSME)

A three-duct Space Shuttle Main Engine (SSME) Hot Gas Manifold geometry code was developed for use. The methodology of the program is described, recommendations on its implementation made, and an input guide, input deck listing, and a source code listing provided. The code listing is strewn with an abundance of comments to assist the user in following its development and logic. A working source deck will be provided. A thorough analysis was made of the proper boundary conditions and chemistry kinetics necessary for an accurate computational analysis of the flow environment in the SSME fuel side preburner chamber during the initial startup transient. Pertinent results were presented to facilitate incorporation of these findings into an appropriate CFD code. The computation must be a turbulent computation, since the flow field turbulent mixing will have a profound effect on the chemistry. Because of the additional equations demanded by the chemistry model it is recommended that for expediency a simple algebraic mixing length model be adopted. Performing this computation for all or selected time intervals of the startup time will require an abundance of computer CPU time regardless of the specific CFD code selected.

Source record↗