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At least 505 records · Page 28

Assimilation of SMAP Brightness Temperature Observations in the GEOS Land–Atmosphere Data Assimilation System

Errors in soil moisture adversely impact the modeling of land–atmosphere water and energy fluxes and, consequently, near-surface atmospheric conditions in atmospheric data assimilation systems (ADAS). To mitigate such errors, a land surface analysis is included in many such systems, although not yet in the currently operational NASA Goddard Earth Observing System (GEOS) ADAS. This article investigates the assimilation of L-band brightness temperature (Tb) observations from the Soil Moisture Active Passive (SMAP) mission in the GEOS weakly coupled land–atmosphere data assimilation system (LADAS) during boreal summer 2017. The SMAP Tb analysis improves the correlation of LADAS surface and root-zone soil moisture versus in situ measurements by ∼0.1–0.26 over that of ADAS estimates; the unbiased root-mean-square error of LADAS soil moisture is reduced by 0.002–0.008 m^3 /m^3 from that of ADAS. Furthermore, the global land average RMSE versus in situ measurements of screen-level air specific humidity (q2m) and daily maximum temperature (T2m_max ) is reduced by 0.05 g/kg and 0.04 K, respectively, for LADAS compared to ADAS estimates. Regionally, the RMSE of LADAS q2m and T2m_max is improved by up to 0.4 g/kg and 0.3 K, respectively. Improvement in LADAS specific humidity extends into the lower troposphere (below ∼700 mb), with relative improvements in bias of 15–25%, although LADAS air temperature bias slightly increases relative to that of ADAS. Finally, the root mean square of the LADAS Tb observation-minus-forecast residuals is smaller by up to ∼0.1 K than in a land-only assimilation system, corroborating the positive impact of the Tb analysis on the modeled land–atmosphere coupling.

microwave remote sensing↗

Seawater Debye Model Function at L-Band and Its Impact on Salinity Retrieval From Aquarius Satellite Data

A model function of seawater, which specifies the dielectric constant of seawater as a function of salinity, temperature, and frequency, is important for the retrieval of sea surface salinity using satellite data. In 2017, a model function has been developed based on measurement data at 1.4134 GHz using a third-order polynomial expression in salinity ( S ) and temperature ( T ). Although the model showed improvements in salinity retrieval, it had an inconsistent behavior between partitioned salinities. To improve the stability of the model, new dielectric measurements of seawater have been made recently over a broad range of salinities and temperatures to expand the data set used for developing the model function. The structure of the model function has been changed from a polynomial expansion in S and T to a physics-based model consisting of a Debye molecular resonance term plus a conductivity term. Each unknown parameter is expressed in S and T based on the expanded measurement data set. Physical arguments have been used to limit the number of unknown coefficients in these expressions to improve the stability of the model function. The new model function has been employed in the retrieval algorithm of the Aquarius satellite mission to obtain a global salinity map. The retrieved salinity using a different model function is compared with in situ data collected by Argo floats to evaluate the impact and the performance of model functions. The results indicate that the new model function has significant improvements in salinity retrieval compared with other existing models.

Seawater↗

Effect of Rain-Adjusted Satellite Sea Surface Salinity on ENSO Predictions from the GMAO S2S Forecast System

ENSO has a significant impact on climate variability throughout the world and so has been the key focus for improving coupled ocean-atmosphere forecasts. Assimilation of altimetry and in situ data lead to improved short-term forecasts of the coupled system. However, few studies have focused on improving the near-surface density/mixing through assimilation of satellite sea surface salinity (SSS). For expediency, most projects that do assimilate SSS do so as if these data were observed at the top model layer instead of at the surface. In rainy regions where buoyant water sits as a fresh lens at the surface, this assumption is likely invalid. Therefore, we adjust SSS so that it more accurately represents the salinity at the first model layer. The Rain Impact Model (RIM) uses a simple diffusion model to determine the near surface salinity gradient (i.e., 1 cm to 5 m). Satellite SSS data are modified using this near-surface salinity gradient, so the salinity values are now valid at the first model layer (we call this SSS@5m). We assess the impact of satellite SSS observations for near-surface dynamics within ocean reanalyses and how these impact dynamical ENSO forecasts using the NASA GMAO S2S coupled system. For all reanalysis experiments, all available along-track sea level and in situ observations are assimilated for 2011 to 2020 using the LETKF scheme (Penny et al., 2013). One reanalysis assimilates Aquarius /SMAP SSS as before. An additional reanalysis is performed assimilating the SSS@5m data. Validation statistics are compared for experiments that assimilate SSS (sub-optimally as before) versus the SSS@5m. We also compare results of coupled forecasts that are initialized from these reanalyses in spring. For all but the big La Niña in 2017, all NINO3.4 forecasts were improved by using the RIM. We will show that improved SSS estimates upgrades density and near-surface mixing leading to more accurate coupled air/sea interaction and better forecasts.

ENSO↗

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.↗

Impact of CAMEX-4 Data Sets for Hurricane Forecasts using a Global Model

This study explores the impact on hurricane data assimilation and forecasts from the use of dropsondes and remote-sensed moisture profiles from the airborne Lidar Atmospheric Sensing Experiment (LASE) system. We show that the use of these additional data sets, above those from the conventional world weather watch, has a positive impact on hurricane predictions. The forecast tracks and intensity from the experiments show a marked improvement compared to the control experiment where such data sets were excluded. A study of the moisture budget in these hurricanes showed enhanced evaporation and precipitation over the storm area. This resulted in these data sets making a large impact on the estimate of mass convergence and moisture fluxes, which were much smaller in the control runs. Overall this study points to the importance of high vertical resolution humidity data sets for improved model results. We note that the forecast impact from the moisture profiling data sets for some of the storms is even larger than the impact from the use of dropwindsonde based winds.

Kamineni, Rupa↗

Thermal Model Performance for the James Webb Space Telescope OTIS Cryo-Vacuum Test

The James Webb Space Telescope (JWST), set to launch in mid-2020, is currently undergoing a series of system-level environmental tests to verify its workmanship and end-to-end functionality. As part of this series, the Optical Telescope Element and Integrated Science Instrument Module (OTIS) Cryo-Vacuum (CV) test, the most complex cryogenic test executed to date by NASA, has recently been completed at the Johnson Space Center's Chamber A facility. The OTIS CV test was intended as a comprehensive test of the integrated instrument and telescope systems to fully understand its optical, structural, and thermal performance within its intended flight environment. Due to its complexity, extensive pre-test planning was required to ensure payload safety and compliance with all limits and constraints. A system-level pre-test thermal model was constructed which fully captured the behavior of the payload, ground support equipment, and surrounding test chamber. This thermal model simulated both the transient cooldown to and warmup from a 20 K flight-like environment, as well as predicted the payload performance at cryo-stable conditions. The current work is an assessment of thermal model pre-test prediction performance against actual payload response during the OTIS CV test. Overall, the thermal model performed exceedingly well at predicting schedule and payload response. Looking in depth, this work examines both the benefits and shortcomings of assumptions made pre-test to simplify model execution when compared against test data. It explores in detail the role of temperature-dependent emissivities during transition to cryogenic temperatures, as well as the impact that model geometry simplifications have on tracking of critical hardware limits and constraints. This work concludes with a list of recommendations to improve the accuracy of thermal modeling for future large cryogenic tests. The insight gained from the OTIS CV test thermal modeling will benefit planning and execution for upcoming cryogenic missions.

Testing↗

Thermal Model Performance for the James Webb Space Telescope OTIS Cryo-Vacuum Test

The James Webb Space Telescope (JWST), set to launch in early 2019, is currently undergoing a series of system-level environmental tests to verify its workmanship and end-to-end functionality. As part of this series, the Optical Telescope Element and Integrated Science Instrument Module (OTIS) Cryo-Vacuum (CV) test, the most complex cryogenic test executed to date by NASA, has recently been completed at the Johnson Space Center's Chamber A facility. The OTIS CV test was intended as a comprehensive test of the integrated instrument and telescope systems to fully understand its optical, structural, and thermal performance within its intended flight environment. Due to its complexity, extensive pre-test planning was required to ensure payload safety and compliance with all limits and constraints. A system-level pre-test thermal model was constructed which fully captured the behavior of the payload, ground support equipment, and surrounding test chamber. This thermal model simulated both the transient cooldown to and warmup from a 20K flight-like environment, as well as predicted the payload performance at cryo-stable conditions. The current work is a preliminary assessment of thermal model performance against actual payload response during the OTIS CV test. It examines both the benefits and shortcomings of assumptions made pre-test to simplify model execution when compared against test data. It explores in detail the role of temperature-dependent emissivities during transition to cryogenic temperatures, as well as the impact that model geometry simplifications have on tracking of critical hardware limits and constraints. This work concludes with a list of recommendations to improve the accuracy of thermal modeling for future large cryogenic tests. It is hoped that the insight gained from the OTIS CV test thermal modeling will benefit planning and execution for upcoming cryogenic missions.

JWST↗

Thermal Model Performance for the James Webb Space Telescope OTIS Cryo-Vacuum Test

The James Webb Space Telescope (JWST), set to launch in early 2019, is currently undergoing a series of system-level environmental tests to verify its workmanship and end-to-end functionality. As part of this series, the Optical Telescope Element and Integrated Science Instrument Module (OTIS) Cryo-Vacuum (CV) test, the most complex cryogenic test executed to date by NASA, has recently been completed at the Johnson Space Center’s Chamber A facility. The OTIS CV test was intended as a comprehensive test of the integrated instrument and telescope systems to fully understand its optical, structural, and thermal performance within its intended flight environment. Due to its complexity, extensive pre-test planning was required to ensure payload safety and compliance with all limits and constraints. A system-level pre-test thermal model was constructed which fully captured the behavior of the payload, ground support equipment, and surrounding test chamber. This thermal model simulated both the transient cooldown to and warmup from a 20K flight-like environment, as well as predicted the payload performance at cryo-stable conditions. The current work is a preliminary assessment of thermal model performance against actual payload response during the OTIS CV test. Overall, the thermal model performed exceedingly well at predicting schedule and payload response. Looking in depth, this work examines both the benefits and shortcomings of assumptions made pre-test to simplify model execution when compared against test data. It explores in detail the role of temperature-dependent emissivities during transition to cryogenic temperatures, as well as the impact that model geometry simplifications have on tracking of critical hardware limits and constraints. This work concludes with a list of recommendations to improve the accuracy of thermal modeling for future large cryogenic tests. It is hoped that the insight gained from the OTIS CV test thermal modeling will benefit planning and execution for upcoming cryogenic missions.

Yang, Kan↗

Formation of ureilites by impact-melting of cabonaceous chondritic material

Ureilites are modeled as impact-melt products of CV-chondrite-like material. This model is consistent with the brecciated nature and cumulate textures of ureilites, O-isotopic constraints (which indicate ureilite derivation from an isotopically heterogeneous body like the CV-chondrite parent), the high abundance of planetary-type noble gases, and the relatively high concentrations of siderophile and chalcophile elements (indicating incomplete separation of metal-sulfide from silicate). Each ureilite may have been derived from a separate cratering event.

Rubin, Alan E.↗

Risk Estimation of Threatening Asteroids

When faced with the question of designing an asteroid deflection mission or with the decision of launching it, significant uncertainties are present in the asteroid’s physical properties, and its orbit solution. The success of the deflection mission relies heavily on these aspects. For example, a heavier than expected asteroid will reduce the imparted deflection DV. So will a larger porosity value by reducing the beta factor [1]. Here, we present a new capability that estimates asteroid impact risk under consideration of these uncertainties. The new method samples the uncertainty space along multiple dimensions, performs a predetermined deflection, propagates the deflected samples to the Earth, models the impact damage, and estimates the overall risk outcome. The work builds on the Probabilistic Asteroid Impact Risk (PAIR) assessment tool [2] by including orbital uncertainty and deflection capabilities. We demonstrate this risk estimation approach for threatening asteroids using the example of the fictitious impactor 2019 PDC. Such analysis provides a quantitative basis for the work of decision makers and disaster managers. It may further find application in areas such as mitigation mission planning where projected post-mitigation risk can be compared to premitigation levels as a means of cost-benefit analysis formitigation options.

Rumpf, Clemens↗

Incorporation of Failure Into an Orthotropic Three-Dimensional Model with Tabulated Input Suitable for Use in Composite Impact Problems

The need for accurate material models to simulate the deformation, damage and failure of polymer matrix composites under impact conditions is becoming critical as these materials are gaining increased use in the aerospace and automotive communities. The aerospace community has identified several key capabilities which are currently lacking in the available material models in commercial transient dynamic finite element codes. To attempt to improve the predictive capability of composite impact simulations, a next generation material model is being developed for incorporation within the commercial transient dynamic finite element code LS-DYNA. The material model, which incorporates plasticity, damage and failure, utilizes experimentally based tabulated input to define the evolution of plasticity and damage and the initiation of failure as opposed to specifying discrete input parameters such as modulus and strength. The plasticity portion of the orthotropic, three-dimensional, macroscopic composite constitutive model is based on an extension of the Tsai-Wu composite failure model into a generalized yield function with a non-associative flow rule. For the damage model, a strain equivalent formulation is used to allow for the uncoupling of the deformation and damage analyses. In the damage model, a semi-coupled approach is employed where the overall damage in a particular coordinate direction is assumed to be a multiplicative combination of the damage in that direction resulting from the applied loads in various coordinate directions. For the failure model, a tabulated approach is utilized in which a stress or strain based invariant is defined as a function of the location of the current stress state in stress space to define the initiation of failure. Failure surfaces can be defined with any arbitrary shape, unlike traditional failure models where the mathematical functions used to define the failure surface impose a specific shape on the failure surface. In the current paper, the complete development of the failure model is described and the generation of a tabulated failure surface for a representative composite material is discussed.

Impact↗

Limitations in Representation of Physical Processes Prevents Successful Simulation of PM2.5 During KORUS-AQ

High levels of fine particulate matter (PM2.5) pollution in East Asia often exceed local air quality standards. Observations from the Korea United States-Air Quality (KORUS-AQ) field campaign in May and June 2016 showed that development of extreme pollution (haze) occurred through a combination of long-range transport and favorable meteorological conditions that enhanced local production of PM2.5. Atmospheric models often have difficulty simulating PM2.5 chemical composition during haze, which is of concern for the development of successful control measures. We use observations from KORUS-AQ to examine the ability of the GEOS-Chem chemical transport model to simulate PM2.5 composition throughout the campaign and identify the mechanisms driving the pollution event. At the surface, the model underestimates sulfate by -64% but overestimates nitrate by +36%. The largest underestimate in sulfate occurs during the pollution event, where models typically struggle to generate elevated sulfate concentrations due to missing heterogeneous chemistry in aerosol liquid water in the polluted boundary layer. Hourly surface observations show that the model nitrate bias is driven by an overestimation of the nighttime peak. In the model, nitrate formation is limited by the supply of nitric acid, which is biased by +100% against aircraft observations. We hypothesize that this is due to a large missing sink, which we implement here as a factor of five increase in dry deposition. We show that the resulting increased deposition velocity is consistent with observations of total nitrate as a function of photochemical age. The model does not account for factors such as the urban heat island effect or the heterogeneity of the built-up urban landscape resulting in insufficient model turbulence and surface area over the study area that likely results in insufficient dry deposition. Other species such as NH3 could be similarly affected but were not measured during the campaign. Nighttime production of nitrate is driven by NO2 hydrolysis in the model, while observations show that unexpectedly elevated nighttime ozone (not present in the model) should result in N2O5 hydrolysis as the primary pathway. The model is unable to represent nighttime ozone due to an overly rapid collapse of the afternoon mixed layer and excessive titration by NO. We attribute this to missing nighttime heating driving deeper nocturnal mixing that would be expected to occur in a city like Seoul. This urban heating is not considered in air quality models run at large enough scales to treat both local chemistry and long-range transport. Key model failures in simulating nitrate, mainly overestimated daytime nitric acid, incorrect representation of nighttime chemistry, and an overly shallow and insufficiently turbulent nighttime mixed layer, exacerbate the model’s inability to simulate the buildup of PM2.5 during haze pollution. To address the underestimate in sulfate most evident during the haze event, heterogeneous aerosol uptake of SO2 is added to the model which previously only considered aqueous production of sulfate from SO2 in cloud water. Implementing a simple parameterization of this chemistry improves the model abundance of sulfate but degrades the SO2 simulation implying that emissions are underestimated. We find that improving model simulations of sulfate has direct relevance to determining local vs. transboundary contributions to PM2.5. During the haze pollution event, the inclusion of heterogeneous aerosol uptake of SO2 decreases the fraction of PM2.5 attributable to long-range transport from 66% to 54%. Locally-produced sulfate increased from 1% to 25% of locally-produced PM2.5, implying that local emissions controls would have a larger effect than previously thought. However, this additional uptake of SO2 is coupled to the model nitrate prediction which affects the aerosol liquid water abundance and chemistry driving sulfate-nitrate-ammonium partitioning. An additional simulation of the haze pollution with heterogeneous uptake of SO2 to aerosol and simple improvements to the model nitrate simulation results in 30% less sulfate due to 40% less nitrate and aerosol water, and results in an underestimate of sulfate during the haze event. Future studies need to better consider the impact of model physical processes such as dry deposition and nighttime boundary layer mixing on the simulation of nitrate and the effect of improved nitrate simulations on the overall simulation of secondary inorganic aerosol (sulfate+nitrate+ammonium) in East Asia. Foreign emissions are rapidly changing, increasing the need to understand the impact of local emissions on PM2.5 in South Korea to ensure continued air quality improvements.

Katherine R. Travis↗

Development of Computer Models for the Assessment of Foreign Body Impact Events on Composite Structures

The objective of this project was to model the 5-3/4 inch pressure vessels used on the NASA RTOP program in an attempt to learn more about how impact damage forms and what are the residual effects of the resulting damage. A global-local finite element model was developed for the bottle and the states of stress in the bottles were determined down to the constituent level. The experimental data that was generated on the NASA RTOP program was not in a form that enabled the model developed under this grant to be correlated with the experimental data. As a result of this exercise it is recommended that an experimental program be designed using statistical design of experiment techniques to generate data that can be used to isolate the phenomenon that control the formation of impact damage. This data should include residual property determinations so that models for post impact structural integrity can be developed. It is also recommended that the global-local methodology be integrated directly into the finite element code. This will require considerable code development.

Bucinell, Ronald B.↗

The size distributions of fragments ejected at a given velocity from impact craters

The mass distribution of fragments that are ejected at a given velocity for impact craters is modeled to allow extrapolation of laboratory, field, and numerical results to large scale planetary events. The model is semi-empirical in nature and is derived from: (1) numerical calculations of cratering and the resultant mass versus ejection velocity, (2) observed ejecta blanket particle size distributions, (3) an empirical relationship between maximum ejecta fragment size and crater diameter, (4) measurements and theory of maximum ejecta size versus ejecta velocity, and (5) an assumption on the functional form for the distribution of fragments ejected at a given velocity. This model implies that or planetary impacts into competent rock, the distribution of fragments ejected at a given velocity is broad, e.g., 68% of the mass of the ejecta at a given velocity contains fragments having a mass less than 0.1 times a mass of the largest fragment moving at that velocity. The broad distribution suggests that in impact processes, additional comminution of ejecta occurs after the upward initial shock has passed in the process of the ejecta velocity vector rotating from an initially downward orientation. This additional comminution produces the broader size distribution in impact ejecta as compared to that obtained in simple brittle failure experiments.

Okeefe, J. D.↗

The size distributions of fragments ejected at a given velocity from impact craters

The mass distribution of fragments that are ejected at a given velocity for impact craters is modeled to allow extrapolation of laboratory, field, and numerical results to large scale planetary events. The model is semi-empirical in nature and is derived from: (1) numerical calculations of cratering and the resultant mass versus ejection velocity, (2) observed ejecta blanket particle size distributions, (3) an empirical relationship between maximum ejecta fragment size and crater diameter, (4) measurements and theory of maximum ejecta size versus ejecta velocity, and (5) an assumption on the functional form for the distribution of fragments ejected at a given velocity. This model implies that for planetary impacts into competent rock, the distribution of fragments ejected at a given velocity is broad, e.g., 68 percent of the mass of the ejecta at a given velocity contains fragments having a mass less than 0.1 times a mass of the largest fragment moving at that velocity. The broad distribution suggests that in impact processes, additional comminution of ejecta occurs after the upward initial shock has passed in the process of the ejecta velocity vector rotating from an initially downward orientation. This additional comminution produces the broader size distribution in impact ejecta as compared to that obtained in simple brittle failure experiments.

O'Keefe, John D.↗

Melting and its relationship to impact crater morphology

Shock-melting features occur on planets at scales that range from micrometers to megameters. It is the objective of this study to determine the extent of thickness, volume geometry of the melt, and relationship with crater morphology. The variation in impact crater morphology on planets is influenced by a broad range of parameters: e.g., planetary density, thermal state, strength, impact velocity, gravitational acceleration. We modeled the normal impact of spherical projectiles on a semi-infinite planet over a broad range of conditions using numerical techniques.

Okeefe, John D.↗

High-Density Plasma Reactors: Simulations for Design

The development of improved and more efficient plasma reactors is a costly process for the semiconductor industry. Until five years ago, the Industry made most of its advancements through a trial and error approach. More recently, the role of computational modeling in the design process has increased. Both conventional computational fluid dynamics (CFD) techniques like Navier-Stokes solvers as well as particle simulation methods are used to model plasma reactor flowfields. However, since high-density plasma reactors generally operate at low gas pressures on the order of 1 to 10 mTorr, a particle simulation may be necessary because of the failure of CFD techniques to model rarefaction effects. The direct simulation Monte Carlo method is the most widely accepted and employed particle simulation tool and has previously been used to investigate plasma reactor flowfields. A plasma DSMC code is currently under development at NASA Ames Research Center with its foundation as the object-oriented parallel Cornell DSMC code, MONACO. The present investigation is a follow up of a neutral flow investigation of the effects of process parameters as well as reactor design on etch rate and etch rate uniformity. The previous work concentrated on silicon etch of a chlorine flow in a configuration typical of electron cyclotron resonance (ECR) or helical resonator type reactors. The effects of the plasma on the dissociation chemistry were modeled by making assumptions about the electron temperature and number density. The electrons or ions themselves were not simulated.The present work extends these results by simulating the charged species.The electromagnetic fields are calculated such that power deposition is modeled self-consistently. Electron impact reactions are modeled along with mechanisms for charge exchange. An bipolar diffusion assumption is made whereby electrons remain tied to the ions. However, the velocities of tile electrons are allowed to be modified during collisions and are not confined to a Maxwellian distribution. The interaction between the neutral flow and plasma is examined, and results for etch rate uniformity from the previous research and the present plasma simulations are compared.

Hash, David B.↗