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NASA NTRSDate not supplied

International Space Station Bipropellant Plume Contamination Model Update for Short Thruster Pulse Widths

The International Space Station (ISS) Bipropellant Plume Contamination Model has been a vital tool for characterizing the thruster plume-induced contamination environment at the ISS but was not intended to be used for very short thruster pulse widths. This paper presents an updated model that ensures full start-up and shut-down phases are modeled for each thruster firing, when the majority of liquid phase contaminant mass is released. The updated ISS Bipropellant Plume Contamination Model prevents potential under-prediction of thruster plume-induced contamination due to visiting vehicle proximity operations and provides a way to take advantage of thruster start-up and shut-down data performance data gathered during thruster test programs, if available. The International Space Station (ISS) Bipropellant Plume Contamination Model developed by Boeing Space Environments is a semi-empirical model anchored in flight experiment data and has been a vital tool for characterizing the thruster plume-induced contamination environment at the ISS.[1] The current model utilizes flight experiment data from the Plume Impingement Contamination (PIC) and Shuttle Plume Impingement Flight Experiment (SPIFEX) studies, which include Orbiter 3870 N Primary Reaction Control System (PRCS) and Russian 130 N thrusters operating in pulse mode with 80-100 ms.[2] As the next generation of crew and cargo visiting vehicles are developed and arrive at ISS, minimum pulse widths of vehicle thrusters used for ISS proximity operations have decreased significantly below 80 ms. An update to the ISS Bipropellant Contamination Model is needed to prevent potential under-prediction of thruster plume-induced contamination for these very short pulse widths. Contamination due to thruster plumes occurs in the liquid phase (i.e., unburned or partially burned propellant in the plume). Liquid phase releases primarily occur during thruster start-up and shut-down phases, with the steady state phase contributing a small amount to the total contaminant mass released. The current ISS Bipropellant Plume Contamination Model includes functional dependencies on thruster parameters (thrust, mass flow rate, specific impulse (Isp)), distance to receiver surface, and angle off plume centerline. For modeling purposes, contaminant mass released scales linearly with pulse width. This is a conservative approach for pulse widths greater than 80 ms but could under-predict contamination for very short pulse widths (i.e., with little or no steady state phase). This paper presents a model update to add a functional dependency on commanded pulse width to ensure the portion of the pulse spent in start-up and shut-down phases is appropriately modeled, when the majority of liquid phase contaminant mass is released. The updated model prevents potential under-prediction of thruster plume-induced contamination due to visiting vehicle proximity operations while providing a way to take advantage of thruster start-up and shut-down data gathered during test programs, if available. Developing the plume model for a specific thruster using the ISS Bipropellant Plume Contamination Model must be done in consideration of all available thruster performance data. Example thruster data will be used to illustrate this point and options for implementing the model update with existing ISS Bipropellant Plume Contamination Model code will be discussed.

plume contamination↗

DOE OSTI2025

Sensitivities of Large Eddy Simulations of Aerosol Plume Transport and Cloud Response

Abstract Cloud responses to surface‐based sources of aerosol perturbation partially depend on how turbulent transport of the aerosol to cloud base affects the spatial and temporal distribution of aerosol. Here, scenarios of plume injection below a marine stratocumulus cloud are modeled using large eddy simulations coupled to a prognostic bulk aerosol and cloud microphysics scheme. Both passive plumes, consisting of an inert tracer, and active plumes are investigated, where the latter are representative of saltwater droplet plumes such as have been proposed for marine cloud brightening. Passive plume scenarios show higher in‐plume cloud brightness (relative to out‐of‐plume) due to the predominant transport of the passive plume tracer from the near‐surface to the cloud layer within updrafts. These updrafts rise into brighter areas within the cloud deck, even in the absence of an aerosol perturbation associated with an active plume. Comparing albedo at in‐plume to out‐of‐plume locations associates the inert plume with the brightest cloud locations, without any causal effect of the plume on the cloud. Numerical sensitivities are first assessed to establish a suitable model configuration. Then sensitivity to particle injection rate is investigated. Trade‐offs are identified between the number of injected particles and the suppressive effect of droplet evaporation on plume loft and spread. Furthermore, as the near‐field in‐plume brightening effect does not depend significantly on injection rate given a suitable definition of perturbed versus unperturbed regions of the flow, plume area is a key controlling factor on the overall cloud brightening effect of an aerosol perturbation.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Deep learning inversion of gravity data for detection of CO 2 plumes in overlying aquifers

In this work, we developed an effective U-Net based deep learning (DL) model for inversion of surface gravity data on a rectangular grid to predict 2-D high-resolution subsurface CO 2 distribution along a vertical cross-section due to CO 2 leakage through a wellbore within a deep CO 2 storage reservoir. We used synthetic data to model two types of CO 2 leakage scenarios: one CO 2 plume in a shallow aquifer (single plume case), and two plumes present at different depths (double plume case). The 3-D synthetic plume samples were created by sampling among predetermined CO 2 plume depths, saturations, and volumes. The corresponding surface gravity data on a rectangular grid were generated by a 3-D forward model. The U-Net model detected 72% of single-plume samples, and one or both plumes in 75% of double-plume samples. Most of the undetected single plumes have small gravity field strengths below the typical noise level of 5 μGal. This model generated reproducible, reliable predictions with acceptable errors and demonstrated improved spatial resolution over the conventional least-squares inversion. In contrast to the conventional least-squares inversion, which often overestimates the size of its target and underestimates its density, this U-Net model accurately delineated the boundary of a target. Furthermore, this DL inversion detected deep, small, or low saturation CO 2 plumes that are often more difficult to resolve with conventional gravity inversion methods. We note the limitations of this feasibility study, including the use of synthetic data with regular CO 2 plume shapes, and the prediction of a 2-D plume cross-section rather than the full 3-D plume, as well, we recognize the lower detection fraction for double-plume scenarios. Nevertheless, this study demonstrates that DL gravity inversion is a promising and potentially superior method to conventional least-squares inversion. Our U-Net based deep learning inversion approach may be adapted for inversion of other types of geophysical data. DL inversion can facilitate near real-time monitoring of geologic carbon sequestration to provide site operators with prompt information about subsurface CO 2 distribution for risk management and mitigation.

58 GEOSCIENCES↗

NASA NTRS1998

Modeling Macro- and Micro-Scale Turbulent Mixing and Chemistry in Engine Exhaust Plumes

Simulation of turbulent mixing and chemical processes in the near-field plume and plume-vortex regimes has been successfully carried out recently using a reduced gas phase kinetics mechanism which substantially decreased the computational cost. A detailed mechanism including gas phase HOx, NOx, and SOx chemistry between the aircraft exhaust and the ambient air in near-field aircraft plumes is compiled. A reduced mechanism capturing the major chemical pathways is developed. Predictions by the reduced mechanism are found to be in good agreement with those by the detailed mechanism. With the reduced chemistry, the computer CPU time is saved by a factor of more than 3.5 for the near-field plume modeling. Distributions of major chemical species are obtained and analyzed. The computed sensitivities of major species with respect to reaction step are deduced for identification of the dominant gas phase kinetic reaction pathways in the jet plume. Both the near field plume and the plume-vortex regimes were investigated using advanced mixing models. In the near field, a stand-alone mixing model was used to investigate the impact of turbulent mixing on the micro- and macro-scale mixing processes using a reduced reaction kinetics model. The plume-vortex regime was simulated using a large-eddy simulation model. Vortex plume behind Boeing 737 and 747 aircraft was simulated along with relevant kinetics. Many features of the computed flow field show reasonable agreement with data. The entrainment of the engine plumes into the wing tip vortices and also the partial detrainment of the plume were numerically captured. The impact of fluid mechanics on the chemical processes was also studied. Results show that there are significant differences between spatial and temporal simulations especially in the predicted SO3 concentrations. This has important implications for the prediction of sulfuric acid aerosols in the wake and may partly explain the discrepancy between past numerical studies (that employed parabolic or temporal approximations) and the measured data. Finally to address the major uncertainty in the near-field plume modeling related to the plume processing of sulfur compounds and advanced model was developed to evaluate its impact on the chemical processes in the near wake. A comprehensive aerosol model is developed and it is coupled with chemical kinetics and the axisymmetric turbulent jet flow models. The integrated model is used to simulate microphysical processes in the near-field jet plume, including sulfuric acid and water binary homogeneous nucleation, coagulation, non-equilibrium heteromolecular condensation, and sulfur-induced soot activation. The formation and evolution of aerosols are computed and analyzed. The computed results show that a large number of ultra-fine (0.3--0.6 nm in radius) volatile HSO4 - HO embryos are generated in the near-field plume. These embryos further grow in size by self coagulation and condensation. Soot particles can be activated by both heterogeneous nucleation and scavenging of H2SO4-H2O aerosols. These activated soot particles can serve as water condensation nuclei for contrail formation. Conditions under which ice contrails can form behind aircrafts are studied. The sensitivities of the threshold temperature for contrail formation with respect to aircraft propulsion efficiency, relative humidity, and ambient pressure are evaluated. The computed aerosol properties for different extent of fuel sulfur conversion to S(VI) (SO3 and H2SO4) in engine are examined and the results are found to be sensitive to this conversion fraction.

Menon, Suresh↗

NASA NTRS1990

An analytic model of axisymmetric mantle plume due to thermal and chemical diffusion

An analytic model of axisymmetric mantle plumes driven by either thermal diffusion or combined diffusion of both heat and chemical species from a point source is presented. The governing equations are solved numerically in cylindrical coordinates for a Newtonian fluid with constant viscosity. Instead of starting from an assumed plume source, constraints on the source parameters, such as the depth of the source regions and the total heat input from the plume sources, are deduced using the geophysical characteristics of mantle plumes inferred from modelling of hotspot swells. The Hawaiian hotspot and the Bermuda hotspot are used as examples. Narrow mantle plumes are expected for likely mantle viscosities. The temperature anomaly and the size of thermal plumes underneath the lithosphere can be sensitive indicators of plume depth. The Hawaiian plume is likely to originate at a much greater depth than the Bermuda plume. One suggestive result puts the Hawaiian plume source at a depth near the core-mantle boundary and the source of the Bermuda plume in the upper mantle, close to the 700 km discontinuity. The total thermal energy input by the source region to the Hawaiian plume is about 5 x 10(10) watts. The corresponding diameter of the source region is about 100 to 150 km. Chemical diffusion from the same source does not affect the thermal structure of the plume.

Liu, Mian↗

NASA NTRS2006

Processes Influencing Ozone Levels in Alaskan Forest Fires Plumes during Long-Range Transport over the North Atlantic

A case of long-range transport of a biomass burning plume from Alaska to Europe is analyzed using a Lagrangian approach. This plume was sampled several times in the free troposphere over North America, the North Atlantic and Europe by 3 different aircraft during the IGAC Lagrangian 2K4 experiment which was part of the ICARTT/ITOP measurement intensive in summer 2004. Measurements in the plume showed enhanced values of CO, VOCs and NOy, mainly in form of PAN. Observed O3 levels increased by 17 ppbv over 5 days. A photochemical trajectory model, CiTTyCAT, is used to examine processes responsible for the chemical evolution of the plume. The model was initialized with upwind data, and compared with downwind measurements. The influence of high aerosol loading on photolysis rates in the plume is investigated using in-situ aerosol measurements in the plume and lidar retrievals of optical depth as input into a photolysis code (Fast-J), run in the model. Significant impacts on photochemistry are found with a decrease of 18 percent in O3 production and 24 percent in O3 destruction over 5 days when including aerosols. The plume is found to be chemically active with large O3 increases attributed primarily to PAN decomposition during descent of the plume towards Europe. The predicted O3 changes are very dependent on temperature changes during transport, and also, on water vapor levels in the lower troposphere which can lead to O3 destruction. Simulation of mixing/dilution was necessary to reproduce observed pollutants level in the plume. Mixing was simulated using background concentrations from measurements in air masses in close proximity to the plume, and mixing timescales (averaging 6.25 days) were derived from CO changes. Observed and simulated O3/CO correlations in the plume are also compared in order to evaluate the photochemistry in the model. Observed slopes changed from negative to positive over 5 days. This change, which can be attributed largely to photochemistry, is well reproduced by multiple model runs even if slope values are slightly underestimated suggesting small underestimation of photochemical processes. The possible impact of this biomass burning plume on O3 levels in the Europe boundary layer is also examined by running the model for a further 5 days, and comparing with data collected at surface sites, such as Jungfraujoch, which showed small O3 increases and elevated CO levels. The model predicts significant changes in O3 over this 10 days due to photochemistry but the signal is largely lost due to the effects of dilution. However, measurement in several others BB plumes over Europe show that O3 impact of Alaskan fires can be punctually significant over Europe.

Real, E.↗

NASA NTRS2012

Space-based Observational Constraints for 1-D Plume Rise Models

We use a space-based plume height climatology derived from observations made by the Multi-angle Imaging SpectroRadiometer (MISR) instrument aboard the NASA Terra satellite to evaluate the ability of a plume-rise model currently embedded in several atmospheric chemical transport models (CTMs) to produce accurate smoke injection heights. We initialize the plume-rise model with assimilated meteorological fields from the NASA Goddard Earth Observing System and estimated fuel moisture content at the location and time of the MISR measurements. Fire properties that drive the plume-rise model are difficult to estimate and we test the model with four estimates for active fire area and four for total heat flux, obtained using empirical data and Moderate Resolution Imaging Spectroradiometer (MODIS) re radiative power (FRP) thermal anomalies available for each MISR plume. We show that the model is not able to reproduce the plume heights observed by MISR over the range of conditions studied (maximum r2 obtained in all configurations is 0.3). The model also fails to determine which plumes are in the free troposphere (according to MISR), key information needed for atmospheric models to simulate properly smoke dispersion. We conclude that embedding a plume-rise model using currently available re constraints in large-scale atmospheric studies remains a difficult proposition. However, we demonstrate the degree to which the fire dynamical heat flux (related to active fire area and sensible heat flux), and atmospheric stability structure influence plume rise, although other factors less well constrained (e.g., entrainment) may also be significant. Using atmospheric stability conditions, MODIS FRP, and MISR plume heights, we offer some constraints on the main physical factors that drive smoke plume rise. We find that smoke plumes reaching high altitudes are characterized by higher FRP and weaker atmospheric stability conditions than those at low altitude, which tend to remain confined below the BL, consistent with earlier results. We propose two simplified parameterizations for computing injection heights for fires in CTMs and discuss current challenges to representing plume injection heights in large scale atmospheric models.

Martin, Maria Val↗

NASA NTRS2017

Critical Magnetic Field Strengths for Unipolar Solar Coronal Plumes In Quiet Regions and Coronal Holes?

Coronal plumes are bright magnetic funnels that are found in quiet regions and coronal holes that extend high into the solar corona whose lifetimes can last from hours to days. The heating processes that make plumes bright involve the magnetic field at the base of the plume, but their intricacies remain mysterious. Raouafi et al. (2014) infer from observation that plume heating is a consequence of magnetic reconnection at the base, whereas Wang et al. (2016) infer that plume heating is a result of convergence of the magnetic flux at the plume's base, or base flux. Both papers suggest that the base flux in their plumes is of mixed polarity, but do not quantitatively measure the base flux or consider whether a critical magnetic field strength is required for plume production. To investigate the magnetic origins of plume heating, we track plume luminosity in the 171 Å wavelength as well as the abundance and strength of the base flux over the lifetimes of six unipolar coronal plumes. Of these, three are in coronal holes and three are in quiet regions. For this sample, we find that plume heating is triggered when convergence of the base flux surpasses a field strength of approximately 300 − 500 Gauss, and that the luminosity of both quiet region and coronal hole plumes respond similarly to the strength of the magnetic field in the base.

Avallone, Ellis↗

NASA NTRS2021

Airborne and Ground-Based Measurements of Aerosol Optical Depth of Freshly Emitted Anthropogenic Plumes in the Athabasca Oil Sands Region

In this work we report the airborne aerosol optical depth (AOD) from measurements within freshly emitted anthropogenic plumes arising from mining and processing operations in the Athabasca Oil Sands Region (AOSR) in the context of ground-based AERONET climatological daily averaged AODs at Fort McMurray (Alberta, Canada). During two flights on 9 and 18 June 2018, the NASA airborne 4STAR (Spectrometers for Sky-Scanning, Sun-Tracking Atmospheric Research) Sun photometer registered high fine-mode (FM, <1 µm) in-plume AODs of up to 0.4 and 0.9, respectively, in the vicinity of the plume source (<20 km). Particle composition shows that the plumes were associated with elevated concentrations of sulfates and ammonium. These high AODs significantly exceed climatological averages for June and were not captured by the nearby AERONET instrument (mean daily AODs of 0.10±0.01 and 0.07±0.02, maximum AOD of 0.12) due possibly to horizontal inhomogeneity of the plumes, plume dilution and winds which in certain cases were carrying the plume away from the ground-based instrument. The average 4STAR out-of-plume (background) AODs deviated only marginally from AERONET daily averaged values. While 4STAR AOD peaks were generally well correlated in time with peaks in the in situ-measured particle concentrations, we show that differences in particle size are the dominant factor in determining the 4STAR-derived AOD. During the two flights of 24 June and 5 July 2018 when plumes likely travelled distances of 60 km or more, the average 4STAR FM AOD increased by 0.01–0.02 over ∼50 km of downwind particle evolution, which was supported by the increases in layer AODs calculated from the in situ extinction measurements. Based on these observations as well as the increases in organic mass, we attribute the observed AOD increase, at least in part, to secondary organic aerosol formation. The in-plume and out-of-plume AODs for this second pair of flights, in contrast to clear differences in in situ optical and other measurements, were practically indistinguishable and compared favourably to AERONET within 0.01–0.02 AOD. This means that AERONET was generally successful in capturing the background AODs, but missed some of the spatially constrained high-AOD plumes with sources as close as 30–50 km, which is important to note since the AERONET measurements are generally thought to be representative of the regional AOD loading. The fact that industrial plumes can be associated with significantly higher AODs in the vicinity of the emission sources than previously reported from AERONET can potentially have an effect on estimating the AOSR radiative impact.

AERONET↗

DOE OSTI2024

Mixing of the Connecticut River Plume During Ambient Flood Tides: Spatial Heterogeneity and Contributions of Bottom–Generated and Interfacial Mixing

The Connecticut River plume is influenced by energetic ambient tides in the Long Island Sound receiving waters. The objectives of this modeling study are (a) characterizing the spatial heterogeneity of turbulent buoyancy fluxes, (b) partitioning turbulent buoyancy fluxes into bottom-generated and interfacial shear contributions, and (c) quantifying contributions to plume-integrated mixing within the tidal plume. The plume formed during ambient flood tides under low river discharge, spring tides, and no winds is analyzed. Turbulent buoyancy fluxes (B) and depth-integrated B through the plume (Bd) are characterized by pronounced spatial heterogeneity. Strong mixing (Bd ~ 10 –5 -10 –4 m 3 /s 3 ) occurs near the mouth, in the nearfield plume turning region, over shoals, and nearshore shallow areas. Low to moderate mixing (Bd ~ 10 –8 -10 –6 m 3 /s 3 ) occupies half the plume. Buoyancy fluxes are first partitioned based on the depth of the shear stress minimum between plume-generated and bottom-generated shear maxima. Four other tested partitioning methods are based on open channel flow and stratified shear flow parameterizations. Interfacial and bottom-generated shear contribute to different areas of intense and moderate mixing. All methods indicate a significant plume mixing role for bottom-generated mixing, but interfacial mixing is a bigger contributor. Plume-integrated total and interfacial mixing peak at max ambient flood and the timing of peak bottom-generated mixing varies among partitioning methods. Two-thirds of the mixing occurs in concentrated intense mixing areas. A parameter space with the ambient tidal Froude number and plume thickness to depth ratio as axes indicates many tidally modulated plumes are moderately to dominantly influenced by bottom-generated tidal mixing.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRSDate not supplied

Plume Impingement Software Module for Real-Time Proximity Operations

Successfully executing proximity operations in space, such as docking or in-orbit servicing, requires sophisticated spacecraft design that accounts for induced environments. As a chaser vehicle’s attitude control thrusters fire, they create rarefied plumes that can impact the target vehicle, with the potential to overload components, exceed thermal limits, and spin the target vehicle out of control. High-fidelity simulations of the thruster plume impingement environment require the direct simulation Monte Carlo (DSMC) method, but DSMC is too computationally expensive to simulate proximity operations that involve thousands of thruster firings. For this analysis to be tractable, engineering models of the plume flowfield and impingement events are used to simulate these trajectories [1]. Currently, on-orbit plume impingement environments are modeled through an inefficient open-loop analysis cycle where the vehicle’s flight controller and plume impingement teams iterate on the trajectories until they pass the target vehicle’s plume requirements. As complex on-orbit missions evolve and become more frequent, lengthy design cycles will become operational bottlenecks. To address this gap, this work develops an advanced plume impingement module capable of operating at real-time scale that can be integrated with existing mission planning tools and onboard flight systems. The plume module leverages state-of-the-art plume simulation techniques [2] to deliver fast, physics-based impingement predictions in a software architecture that can be tailored to diverse proximity operations scenarios. A prototype of this plume impingement module is built to demonstrate the feasibility of real-time performance. This prototype completes plume impingement calculations in microseconds per target geometry mesh point. The software serves as a foundational capability for plume-aware trajectory design, operational risk assessment, and future autonomous decision-making systems.

Plume Impingement↗

NASA NTRS1991

Low altitude plume impingement handbook

Plume Impingement modeling is required whenever an object immersed in a rocket exhaust plume must survive or remain undamaged within specified limits, due to thermal and pressure environments induced by the plume. At high altitudes inviscid plume models, Monte Carlo techniques along with the Plume Impingement Program can be used to predict reasonably accurate environments since there are usually no strong flowfield/body interactions or atmospheric effects. However, at low altitudes there is plume-atmospheric mixing and potential large flowfield perturbations due to plume-structure interaction. If the impinged surface is large relative to the flowfield and the flowfield is supersonic, the shock near the surface can stand off the surface several exit radii. This results in an effective total pressure that is higher than that which exists in the free plume at the surface. Additionally, in two phase plumes, there can be strong particle-gas interaction in the flowfield immediately ahead of the surface. To date there have been three levels of sophistication that have been used for low altitude plume induced environment predictions. Level 1 calculations rely on empirical characterizations of the flowfield and relatively simple impingement modeling. An example of this technique is described by Piesik. A Level 2 approach consists of characterizing the viscous plume using the SPF/2 code or RAMP2/LAMP and using the Plume Impingement Program to predict the environments. A Level 3 analysis would consist of using a Navier-Stokes code such as the FDNS code to model the flowfield and structure during a single calculation. To date, Level 1 and Level 2 type analyses have been primarily used to perform environment calculations. The recent advances in CFD modeling and computer resources allow Level 2 type analysis to be used for final design studies. Following some background on low altitude impingement, Level 1, 2, and 3 type analysis will be described.

Smith, Sheldon D.↗

NASA NTRS1996

SSME Condition Monitoring Using Neural Networks and Plume Spectral Signatures

For a variety of reasons, condition monitoring of the Space Shuttle Main Engine (SSME) has become an important concern for both ground tests and in-flight operation. The complexities of the SSME suggest that active, real-time condition monitoring should be performed to avoid large-scale or catastrophic failure of the engine. In 1986, the SSME became the subject of a plume emission spectroscopy project at NASA's Marshall Space Flight Center (MSFC). Since then, plume emission spectroscopy has recorded many nominal tests and the qualitative spectral features of the SSME plume are now well established. Significant discoveries made with both wide-band and narrow-band plume emission spectroscopy systems led MSFC to develop the Optical Plume Anomaly Detection (OPAD) system. The OPAD system is designed to provide condition monitoring of the SSME during ground-level testing. The operational health of the engine is achieved through the acquisition of spectrally resolved plume emissions and the subsequent identification of abnormal emission levels in the plume indicative of engine erosion or component failure. Eventually, OPAD, or a derivative of the technology, could find its way on to an actual space vehicle and provide in-flight engine condition monitoring. This technology step, however, will require miniaturized hardware capable of processing plume spectral data in real-time. An objective of OPAD condition monitoring is to determine how much of an element is present in the SSME plume. The basic premise is that by knowing the element and its concentration, this could be related back to the health of components within the engine. For example, an abnormal amount of silver in the plume might signify increased wear or deterioration of a particular bearing in the engine. Once an anomaly is identified, the engine could be shut down before catastrophic failure occurs. Currently, element concentrations in the plume are determined iteratively with the help of a non-linear computer code called SPECTRA, developed at the USAF Arnold Engineering Development Center. Ostensibly, the code produces intensity versus wavelength plots (i.e., spectra) when inputs such as element concentrations, reaction temperature, and reaction pressure are provided. However, in order to provide a higher-level analysis, element concentration is not specified explicitly as an input. Instead, two quantum variables, number density and broadening parameter, are used. Past experience with OPAD data analysis has revealed that the region of primary interest in any SSME plume spectrum lies in the wavelength band of 3300 A to 4330 A. Experience has also revealed that some elements, such as iron, cobalt and nickel, cause multiple peaks over the chosen wavelength range whereas other elements (magnesium, for example) have a few, relatively isolated peaks in the chosen wavelength range. Iteration with SPECTRA as a part of OPAD data analysis is an incredibly labor intensive task and not one to be performed by hand. What is really needed is the "inverse" of the computer code but the mathematical model for the inverse mapping is tenuous at best. However, building generalized models based upon known input/output mappings while ignoring details of the governing physical model is possible using neural networks. Thus the objective of the research project described herein was to quickly and accurately predict combustion temperature and element concentrations (i.e., number density and broadening parameter) from a given spectrum using a neural network. In other words, a neural network had to be developed that would provide a generalized "inverse" of the computer code SPECTRA.

Hopkins, Randall↗

NASA NTRS2001

Thermal Analysis for Orbiter and ISS Plume Impingement on International Space Station

The NASA Reaction Control System (RCS) Plume Model (RPM) is an exhaust plume flow field and impingement heating code that has been updated and applied to components of the International Space Station (ISS). The objective of this study was to use this code to determine if plume environments from either Orbiter PRCS jets or ISS reboost and Attitude Control System (ACS) jets cause thermal issues on ISS component surfaces. This impingement analysis becomes increasingly important as the ISS is being assembled with its first permanent crew scheduled to arrive by the end of fall 2000. By early summer 2001 , the ISS will have a number of major components installed such as the Unity (Node 1), Destiny (Lab Module), Zarya (Functional Cargo Block), and Zvezda (Service Module) along with the P6 solar arrays and radiators and the Z-1 truss. Plume heating to these components has been analyzed with the RPM code as well as additional components for missions beyond Flight 6A such as the Propulsion Module (PM), Mobile Servicing System, Space Station Remote Manipulator System, Node 2, and the Cupola. For the past several years NASA/JSC has been developing the methodology to predict plume heating on ISS components. The RPM code is a modified source flow code with capabilities for scarfed nozzles and intersecting plumes that was developed for the 44 Orbiter RCS jets. This code has been validated by comparison with Shuttle Plume Impingement Flight Experiment (SPIFEX) heat flux and pressure data and with CFD and Method of Characteristics solutions. Previous analyses of plume heating predictions to the ISS using RPM have been reported, but did not consider thermal analysis for the components nor jet-firing histories as the Orbiter approaches the ISS docking ports. The RPM code has since been modified to analyze surface temperatures with a lumped mass approach and also uses jet-firing histories to produce pulsed heating rates. In addition, RPM was modified to include plume heating from ISS jets to ISS components where the jet coordinates are specified, together with the engine cant angle. These latter studies have been focused on the PM with plumes from its reboost and ACS jets impinging on various ISS components and also focused on the Japanese H2 Transfer Vehicle (HTV) with the plumes from its reboost engines impinging on the Cupola window. This paper will present plume heating and surface temperature results on a number of ISS components with and without jet-firing histories, evaluate post-flight data, and describe any potential thermal issues

Rochelle, William C.↗

DOE OSTI2022

Standoff Infrared Measurements of Chemical Plume Dynamics in Complex Terrain Using a Combination of Active Swept-ECQCL Laser Spectroscopy with Passive Hyperspectral Imaging

Chemical plume detection and modeling in complex terrain present numerous challenges. We present experimental results from outdoor releases of two chemical tracers (sulfur hexafluoride and Freon-152a) from different locations in mountainous terrain. Chemical plumes were detected using two standoff instruments collocated at a distance of 1.5 km from the plume releases. A passive long-wave infrared hyperspectral imaging system was used to show time- and space-resolved plume transport in regions near the source. An active infrared swept-wavelength external cavity quantum cascade laser system was used in a standoff configuration to measure quantitative chemical column densities with high time resolution and high sensitivity along a single measurement path. Both instruments provided chemical-specific detection of the plumes and provided complementary information over different temporal and spatial scales. The results show highly variable plume propagation dynamics near the release points, strongly dependent on the local topography and winds. Effects of plume stagnation, plume splitting, and plume mixing were all observed and are explained based on local topographic and wind conditions. Measured plume column densities at distances ~100 m from the release point show temporal fluctuations over ~1 s time scales and spatial variations over ~1 m length scales. The results highlight the need for high-speed and spatially resolved measurement techniques to provide validation data at the relevant spatial and temporal scales required for high-fidelity terrain-aware microscale plume propagation models.

47 OTHER INSTRUMENTATION↗

NASA NTRS2014

Overview of NASA GRCs Green Propellant Infusion Mission Thruster Testing and Plume Diagnostics

The Green Propellant Infusion Mission (GPIM) is sponsored by NASA's Space Technology Mission Directorate (STMD) Technology Demonstration Mission (TDM) office. The goal of GPIM is to advance the technology readiness level of a green propulsion system, specifically, one using the monopropellant, AF-M315E, by demonstrating ground handling, spacecraft processing, and on-orbit operations. One of the risks identified for GPIM is potential contamination of sensitive spacecraft surfaces from the effluents in the plumes of AF-M315E thrusters. NASA Glenn Research Center (GRC) is conducting activities to characterize the effects of AF-M315E plume impingement and deposition. GRC has established individual plume models of the 22-N and 1-N thrusters that will be used on the GPIM spacecraft. The models describe the pressure, temperature, density, Mach number, and species concentration of the AF-M315E thruster exhaust plumes. The models are being used to assess the impingement effects of the AF-M315E thrusters on the GPIM spacecraft. The model simulations will be correlated with plume measurement data from Laboratory and Engineering Model 22-N, AF-M315E thrusters. The thrusters will be tested in a small rocket, altitude facility at NASA GRC. The GRC thruster testing will be conducted at duty cycles representatives of the planned GPIM maneuvers. A suite of laser-based diagnostics, including Raman spectroscopy, Rayleigh spectroscopy, Schlieren imaging, and physical probes will be used to acquire plume measurements of AFM315E thrusters. Plume data will include temperature, velocity, relative density, and species concentration. The plume measurement data will be compared to the corresponding simulations of the plume model. The GRC effort will establish a data set of AF-M315E plume measurements and a plume model that can be used for future AF-M315E applications.

green Propellants↗

DOE OSTI2026

Impact of Forest Canopy Structure on Buoyant Plume Dynamics During Wildland Fires

Heterogeneous forest canopies can generate complex turbulent structures, but in the presence of a fire plume, these interactions are not fully understood. This study investigates the influence of forest canopy heterogeneity on buoyant plume dynamics resulting from surface thermal anomalies representing wildland fires, utilizing Large Eddy Simulation (LES). The Parallelized Large-Eddy Simulation Model (PALM) was employed to simulate six canopy configurations: no canopy, homogeneous canopy, external plume-edge canopy, internal plume-edge canopy, 100 m gap canopy, and 200 m gap canopy. Each configuration was analyzed with and without a static surface heat flux patch of 5000 W ∙ m -2 , resulting in a resting buoyant plume. Simulations were conducted under three crosswind speeds: 0, 5, and 10 m ∙ s -1 . Results show that canopy structure significantly modifies plume behavior, mean flow, and turbulent kinetic energy (TKE) budgets. Plume updraft speed and tilt varied with canopy configuration and crosswind speed. Horizontal pressure gradients associated with plume-atmosphere interaction were modified based on the canopy configuration, resulting in varying crosswind speed reductions at the plume region. Strong momentum absorption was observed above the canopy for the crosswind cases, with the greatest enhancement in the gap canopies. Momentum injection from below the canopy due to the heat source was also observed, resulting in plume structure modulation based on canopy configuration. TKE was found to be the largest in the gap canopy configurations. TKE budget analysis revealed that buoyant production dominated over shear production. At the center of the heat patch, the gap canopy configurations showed enhanced buoyancy within the gap. These results improve our knowledge of fire-canopy-atmosphere interactions that can inform fire models on the impacts of canopy heterogeneity on plume dynamics and ember ejections.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Assessment of integral models for non-Boussinesq lazy plumes using numerical simulations

Integral modelling of turbulent buoyant plumes is crucial for rapid predictions of plume characteristics. While the governing equations are typically derived using self-similarity and a Boussinesq approximation, these assumptions may not hold for plumes originating from finite-area sources with large density ratios. Here, this work evaluates the accuracy of integral-scale models for non-Boussinesq lazy plumes using high-fidelity numerical simulations of turbulent helium plumes. We analyse the plume kinematics by computing vertical fluxes, plume radius and radial profiles, establishing some disparities between common practice and physical accuracy. We identify how the definition of the plume radius changes the perception of the plume structure when the flow is not self-similar and derive a relationship between the flux-based and threshold-based definitions without requiring self-similarity. We then examine the plume dynamics by evaluating the source terms from the governing plume equations. Our results support neglecting diffusive and viscous effects but emphasise the importance of the mean pressure gradient, even in the self-similar regime. Two coefficients need to be modelled: the well-known entrainment coefficient and the lesser-known momentum correction coefficient, which is a correction required for the momentum equation to account for self-similar and slender approximations. The momentum correction coefficient is found to be approximately constant and slightly greater than the assumed value of 1. The standard entrainment coefficient models perform well up to a local Richardson number three times the asymptotic value but overpredict entrainment for larger Richardson numbers. We propose a correction using the known finite limit of entrainment at infinite Richardson number.

Meehan, Michael Alexander [Sandia National Laborat↗