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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS1993

Fuels and Combustion Technology for Advanced Aircraft Engines [Les Propergols et les Systèmes de Combustion pour les Moteurs d'Aéronefs]

The Conference Proceedings contains the 38 papers presented at the Propulsion and Energetics Panel 81st Symposium on "Fuels and Combustion Technology for Advanced Aircraft Engines" which was held from 10th-14th May 1993, in Fiuggi, Italy. The Technical Evaluation Report and the Keynote Address are included at the beginning, and discussions follow most papers. The Symposium was arranged in the following Sessions: Technology Overview Papers (2); Modelling: Pollutant Formation (4); Modelling: Combustor Design (5); High Temperature Fuels and Fuel Systems (6); Combustion Research: Performance (6); Combustion Research: Emissions (5); Fuel Atomization: Diagnostics and Modelling (5); and Combustion Research: Flowfleld and Mixing (4). The last paper is a contribution from Russia not allocated to a session. New technologies for low NOx combustors and advanced high-pressure/high temperature cycle engines result in unique problems in design and performance. There have been significant advances in modelling and diagnostics to aid the development of these technologies. The purpose of the Symposium was to bring together experts from industry, research establishments and universities to discuss fundamental and applied research in these areas as relevant to the development of advanced gas turbine engines, to exchange practical experience and to discuss the state of the art.

Fuels for aircraft↗
DOE OSTI2021

HIBP Applications to Advance Understanding of Plasma Transport Physics (2011-2017) (and subsequently titled) Development of Beam Measurements to Advance Understanding of Transients and Improve Validation (2017-2020) (Final Technical Report)

This is the Final Technical Report for the DoE Measurement Innovation (previously Diagnostic Development) grant DE-SC0006077 titled HIBP Applications to Advance Understanding of Plasma Transport Physics (2011-2017), and subsequently titled Development of Beam Measurements to Advance Understanding of Transients and Improve Validation (2017-2020). The grant was funded by the Office of Fusion Energy Sciences (FES) for the period 1 May 2011–17 July 2020. Work performed through the grant has resulted in diagnostic innovations and new measurement capabilities that will improve understanding of transport, magnetic equilibrium, and electric fields in magnetically confined plasmas. We have developed novel hardware and advanced techniques to expand beam-based diagnostic capabilities, and extend measurements to new operating regimes. Some have been realized using a Heavy Ion Beam Probe (HIBP) having traditional features, while other applications have joined our innovations with subsets of advantageous HIBP features. This work has established smaller, more economical detection systems and, in doing so, may enable substantial extension of scenarios in which beam-based diagnostics are deployed. Key Measurement Innovations include: Computer Models and Simulations of HIBP Applications-Computer modeling and simulating of HIBP applications is central to predicting interaction of beam particles with plasmas, designing diagnostic systems, and anticipating measurement characteristics. We have extended the capability and improved measurement fidelity of the HIBP diagnostic on the Madison Symmetric Torus (MST) reversed field pinch (RFP); simulated feasibility of HIBP operation in the Helically Symmetric eXperiment (HSX) optimized stellarator; and investigated the plausibility of HIBP measurements in the ASDEX Upgrade tokamak. We have also developed a new technique that uses ion optics to model a finite phase-space beam. It yields more realistic (than traditional method) estimates of sample volume characteristics, which influence measurement resolution and sensitivity. Extension of Diagnostic Capabilities and Measurements on the MST RFP-Capabilities have been extended using the first and only HIBP installation on an RFP. Challenges associated with operation of the diagnostic on MST include the three-dimensional nature of particle trajectories, temporal topology and amplitude changes in the plasma equilibrium, and strong particle and radiative emission from the plasma. We have addressed these challenges through development of detailed and higher precision diagnostic simulations, calibrated subtraction of noise to resolve secondary ion signals, and implementation of hardware that enables higher fidelity measurement of plasma fluctuations. Development of New Hardware and Measurement Techniques - We have advanced beam-based measurement capabilities via development of new detectors and techniques to determine the poloidal magnetic flux ψ in the plasma, and enable placement of detectors close to the plasma and thus allow a smaller and less expensive diagnostic. We have demonstrated measurement of ψ, an ability that was made possible by development of highly effective noise reduction techniques. We also modeled the effect of non-ideal and instrumentation effects by developing a virtual (simulated) diagnostic. Application of beam-based diagnostics on various devices and multiple magnetic configurations (e.g. stellarator, tokamak, and reversed field pinch) enables investigation of critical physics issues and measurements resulting in the broad parameter space data needed to test and validate theory & modeling.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Analysis of streaked images of x-ray self-emission in laser-driven spherical implosions

Imaging of x-ray self-emission provides a powerful in situ measurement of the spatial and temporal evolution of high-energy-density plasmas. However, interpretation of these measurements requires detailed understanding of the data-generating process. This work presents a case study in the interpretation of x-ray self-emission data for the specific application of streaked one-dimensional slit imaging of spherical laser-driven implosions. A comprehensive generative model of the streaked slit-imaging diagnostic is developed including detailed treatments of the radiation transfer, photometrics, and photostatistics associated with the measurement. The model is used to generate realistic synthetic streaked images and to analyze experimental streaked images to extract important physical quantities of interest. An example analysis of streaked images from implosion experiments on the OMEGA laser is presented, where the model developed in this work is used to constrain the trajectory and peak velocity of the implosion using Bayesian inference.

Bayesian inference↗
NASA NTRS2003

A Tabletop Tool for Modeling Life Support Systems

This paper describes the development plan for a comprehensive research and diagnostic tool for aspects of advanced life support systems in space-based laboratories. Specifically it aims to build a high fidelity tabletop model that can be used for the purpose of risk mitigation, failure mode analysis, contamination tracking, and testing reliability. We envision a comprehensive approach involving experimental work coupled with numerical simulation to develop this diagnostic tool. It envisions a 10% scale transparent model of a space platform such as the International Space Station that operates with water or a specific matched index of refraction liquid as the working fluid. This allows the scaling of a 10 ft x 10 ft x 10 ft room with air flow to 1 ft x 1 ft x 1 ft tabletop model with water/liquid flow. Dynamic similitude for this length scale dictates model velocities to be 67% of full-scale and thereby the time scale of the model to represent 15% of the full- scale system; meaning identical processes in the model are completed in 15% of the full- scale time. The use of an index matching fluid (fluid that matches the refractive index of cast acrylic, the model material) allows making the entire model (with complex internal geometry) transparent and hence conducive to non-intrusive optical diagnostics. So using such a system one can test environment control parameters such as core flows (axial flows), cross flows (from registers and diffusers), potential problem areas such as flow short circuits, inadequate oxygen content, build up of other gases beyond desirable levels, test mixing processes within the system at local nodes or compartments and assess the overall system performance. The system allows quantitative measurements of contaminants introduced in the system and allows testing and optimizing the tracking process and removal of contaminants. The envisaged system will be modular and hence flexible for quick configuration change and subsequent testing. The data and inferences from the tests will allow for improvements in the development and design of next generation life support systems and configurations.

Ramachandran, N.↗
DOE OSTI2022

Analytics-at-scale of Sensor Data for Digital Monitoring in Nuclear Plants (3 rd Annual Report)

Nuclear power plants collect and store large volumes of heterogeneous data from various components and systems. With recent advances in machine learning (ML) techniques, these data can be leveraged to develop diagnostic and short-term forecasting models to better predict future equipment condition. Maintenance operations can then be planned in advance whenever degraded performance is predicted, thus resulting in fewer unplanned outages and the optimization of maintenance activities. This enables lower maintenance costs and improves the overall economics of nuclear power. This report primarily focuses on developing a short-term forecasting process that leverages a feature selection process to distill large volumes of heterogeneous data and predict specific equipment parameters. A variety of feature selection methods, including Shapley Additive Explanations (SHAP) and variance inflation factor (VIF), were used to select the optimal features as inputs for three ML methods: long short-term memory (LSTM) networks, support vector regression (SVR), and random forest (RF). Each combination of model and input features was used to predict a pump bearing temperature both 1 and 24 hours in advance, based on actual plant system data. The optimal inputs for the LSTM and SVR were selected using the SHAP values, while the optimal input for the RF consisted solely of the response variable itself. Each model produced similar 1-hour-ahead predictions, with root mean square errors (RMSEs) of roughly 0.006. For the 24-hour-ahead predictions, differences could be seen between LSTM, SVR, and RF, as reflected by model performances of 0.036 ± 0.014, 0.0026 ± 0, and 0.063 ± 0.004 RMSE, respectively. As big data and continuous online monitoring become more widely available, the proposed feature selection process can be used for many applications beyond the prediction of process parameters within nuclear infrastructure. This report summarizes the Fiscal Year 2021 research progress encompassing the (1) data cleaning and feature selection necessary for ML applications; (2) development of short-term forecasting models to predict future plant process parameters for both single and multiple time steps ahead; and (3) validation of the feature selection methods and short-term forecasting models given new data from different systems.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

ARM data-oriented metrics and diagnostics package for climate model evaluation (ARM-DIAGS-V3) version 3

A Python-based metrics and diagnostics package is currently being developed by the ARM Infrastructure Team at Lawrence Livermore National Laboratory to facilitate the use of long-term high frequency measurements from the ARM program in evaluating the regional climate simulation of clouds, radiation, precipitation, and aerosols. This metrics and diagnostics package computes climatological means of targeted climate model simulation and generates tables and plots for comparing the model simulation with ARM observational data. The CMIP model data sets are also included in the package to enable model inter-comparison as demonstrated in Zhang et al. (2018) and Zhang et al. (2020). The mean of the CMIP model can be served as a reference for individual models. Basic performance metrics are computed to measure the accuracy of mean state and variability of climate models. The evaluated physical quantities include cloud fraction, temperature, relative humidity, cloud liquid water path, total column water vapor, precipitation, sensible and latent heat fluxes, aerosol optical depth, and radiative fluxes, with plan to extend to more fields, such as the evaluation of model simulated aerosol physicochemical properties and cloud microphysics properties. Process-oriented diagnostics focusing on aerosol, cloud, and precipitation-related phenomena are also being developed for the evaluation and development of specific model physical parameterizations. In addition to the Southern Great Plains (SGP), North Slope of Alaska (NSA) and Tropical Western Pacific (TWP) atmospheric observatories in the ARMDIAGS version 2.0, the version 3.0 package have extended to the data collected at the ARM Eastern North Atlantic (ENA) atmospheric observatory and the Observation and Modeling of the Green Ocean Amazon (GOAMAZON) field campaign. The metrics and diagnostics package are currently built upon standard Python libraries and additional Python packages developed by DOE (CDAT). The ARM metrics and diagnostic package is available publicly with the hope that it can serve as an easy entry point for climate modelers to compare their models with ARM data. In this report, we first provide an overview of major metrics in section 2. The input data, which constitutes the core content of the metrics and diagnostics package, is summarized in section 3. A user's guide documenting the workflow/structure of the version 3.0 codes and including step-by-step instruction for running the package is described in section 4.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1995

Low-order nonlinear dynamic model of IC engine-variable pitch propeller system for general aviation aircraft

This paper presents a dynamic model of an internal combustion engine coupled to a variable pitch propeller. The low-order, nonlinear time-dependent model is useful for simulating the propulsion system of general aviation single-engine light aircraft. This model is suitable for investigating engine diagnostics and monitoring and for control design and development. Furthermore, the model may be extended to provide a tool for the study of engine emissions, fuel economy, component effects, alternative fuels, alternative engine cycles, flight simulators, sensors, and actuators. Results show that the model provides a reasonable representation of the propulsion system dynamics from zero to 10 Hertz.

Richard, Jacques C.↗
DOE OSTI2023

Quality Assurance Project Plan for the Salish Sea Model – Continuing Development of New Capabilities and Applications: European Green Crab (EGC) Larval Transport, Coupling to VELMA and Atlantis, Performance Improvements and Diagnostic Applications

This quality assurance project plan (QAPP) is for proposed FY24-FY27 efforts to (a) develop/expand a predictive European Green Crab (EGC) larval dispersal model for the Salish Sea, (b) add linkage between VELMA (Visualizing Ecosystem Land Management Assessments) watershed model and Atlantis model (ecosystem dynamics and food web) through SSM, and (c) continue SSM capability development through the addition of metals, harmful algal blooms (HABs), and FVCOM-LTRANS (Lagrangian Larval Transport) modules.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Geomechanical and Hydrogeological Evaluation of a Shallow Hydraulic Fracture at the Devine Fracture Pilot Site, Medina County, Texas

UT-Austin’s Devine Fracture Pilot Site, 50 miles southwest of San Antonio, Texas, has been targeted for a comprehensive, multidisciplinary development of fracture diagnostic techniques that are cross-validated by ground-truth data acquisition near a recently created, 175-ft-deep, horizontal hydraulic fracture (Ahmadian et al. 2018 Demonstration of proof of concept of electromagnetic geophysical methods for high resolution illumination of induced fracture networks. In Proceedings of the SPE Hydraulic Fracturing Technology Conference and Exhibition, The Woodlands, Texas, USA, 23–25 January 2018. SPE-189858-MS.). To evaluate the fracture diagnostic methods at this site, we conducted injection tests with a predefined volumetric flow-rate profile, resembling a diagnostic fracture injection test on September 2020. Subsequently, we developed hydrogeological and geomechanical models based on flow-rate and bottomhole-pressure measurements. History-matching efforts using a simplified layer-cake hydrogeological model resulted in the field-scale formation permeability of 9.87 × 10 –15 m 2 (10 mD) and Darcy-scale fracture permeability. The analysis of the bottomhole pressure and injection-rate history showed that (1) the newly created horizontal fracture was closed adjacent to the injection well pre-injection and (2) the initial pump-pressure increase at a nominal volumetric injection rate led to near-well fracture reopening, fluid conductivity increase, and abrupt injection-rate increase. To overcome hydrogeological-model limitations of predicting fracture reopening throughout injection, we extended the modeling to a finite-element, poroelastic analysis of horizontal-fracture growth using a cohesive-zone model. Using this fracture-reopening model, we improved the history match of the transient-pressure response during the experiment by adjusting the hydromechanical properties. Furthermore, post-injection pressure transient analyses helped reduce uncertainty in the overburden-stress gradient, and the initial hydraulic-fracturing simulation verified the plausibility of achieving the surveyed propped fracture area.

02 PETROLEUM↗
NASA NTRS2017

Optical Diagnostic Imaging of Multi-Rocket Plume-Induced Base Flow Environments

Non-intrusive optical diagnostic imaging was used for the first time to visualize multi-rocket plume-induced reacting base flows to simulate launch vehicle ascent from sea-level to 250,000 ft. In particular, planar laser induced florescence (PLIF) and infrared (IR) imaging were implemented for the first time to visualize and quantify base flow and rocket plume environments from sub-scale, short-duration propulsion models within a shock tunnel facility. This report discusses the successful imaging diagnostic methods for capturing base flow features and dynamics as a function of altitude. Important base flow and plume features were captured with PLIF and IR diagnostics to develop a conceptual base flow physics model. This imaging data specifically provides insight into the Space Launch System vehicle core-stage and Exploration Upper Stage base environments and further validates short-duration ground test techniques and computational modeling.

Mehta, Manish↗
NASA NTRS1986

Modification of a variational objective analysis model for new equations for pressure gradient and vertical velocity in the lower troposphere and for spatial resolution and accuracy of satellite data

Since late 1982 NASA has supported research to develop a numerical variational model for the diagnostic assimilation of conventional and space-based meteorological data. In order to analyze the model components, four variational models are defined dividing the problem naturally according to increasing complexity. The first of these variational models (MODEL I), the subject of this report, contains the two nonlinear horizontal momentum equations, the integrated continuity equation, and the hydrostatic equation. This report summarizes the results of research (1) to improve the way the large nonmeteorological parts of the pressure gradient force are partitioned between the two terms of the pressure gradient force terms of the horizontal momentum equations, (2) to generalize the integrated continuity equation to account for variable pressure thickness over elevated terrain, and (3) to introduce horizontal variation in the precision modulus weights for the observations.

Achtemeier, G. L.↗
NASA NTRS1987

Sensor-based diagnosis using knowledge of structure and function

A system for fault detection and isolation called LES, developed at the Kennedy Space Center for the Space Shuttle's Launch Processing System, is a well-developed diagnostic system that is simultaneously model-based and sensor-based. This experiment has led to a surprising result: the failure of a sensor can not only be handled in precisely the same way as the failure of any other object, but may present an especially easy case. Classical rule-based diagnostic systems need to find out whether or not their sensors are telling them the truth before they can safely draw inferences from them. By contrast, while LES does treat sensors as a special case, it does so only because there may exist a short cut that allows them to be handled more simply than other objects. LES uses both structural and functional knowledge, and has found cases in which the structural knowledge can be economically replaced by the judicious use of functional relationships; LES' functional relationships are stored in exactly one place, so they must be inverted to determine hypothetical values for possibly faulty objects. The inversion process has been extended to include conditional functions not normally considered to have inverses.

Scarl, Ethan A.↗
NASA NTRS1995

Investigation of infra-red and nonequilibrium air radiation

This report describes progress on the first year of a research program on the infrared radiation of air plasmas conducted in the High Temperature Gasdynamics Laboratory at Stanford University. This program is intended to investigate the masking of infrared signatures by the air plasma formed behind the bow shock of high velocity missiles. To this date, the radiative emission of air plasmas in the infrared has been the object of few experimental investigations, and although several infrared systems are already modeled in radiation codes such as NEQAIR, measurements are required to validate numerical predictions and indicate whether all transitions of importance are accounted for. The present program is motivated by the fact that 9 excited states (A, B, C, D, B', F, H, and H') of NO radiate in the infrared, especially between 1 and 1.5 microns where at least 9 transitions involving can be observed. Because these IR transitions are relatively well separated from each other, excited NO states concentrations can be easily measured, thus providing essential information on excited-state chemistry for use in optical diagnostics or in electronic excitation model validation. Developing accurate collisional-radiative models for these excited NO states is of importance as the UV-VUV transitions of NO (beta, gamma, epsilon, beta prime, gamma prime) produce a major, if not dominant, fraction of the radiation emitted by air plasmas. During the first year of the program, research has focused on the spectral range 1.0 to 1.5 microns, as detailed in Section 2 of this report. The measurements, conducted in a 50 kW radio-frequency inductively coupled plasma torch operating on air at atmospheric pressure, extend previous shock tube investigations by Wray to a wider spectral range (1.0 to 1.5 microns vs 0.9 to 1.2 microns) and higher temperatures (7600 K in the plasma torch versus 6700 K in the shock-tube). These higher temperatures in the present experiment have made it possible to observe high-lying excited NO states that were previously undetectable. These measurements are currently being extended up to 5 microns, with particular attention paid to the rovibronic bands of ground state NO, molecular continua, CO transitions, and other systems of importance. Publications and presentations resulting from or related to this work are cited in Section 3, and Section 4 lists the personnel who contributed to this report.

Kruger, Charles H.↗
DOE OSTI2024

Forward Modeling of Gamma Reaction History Signatures From Anticipated Deuterium-Tritium Filled MagLIF Implosions on Sandia’s Z-Machine

Nuclear reaction history measurements provide a bang time and burn width of Inertial Confinement Fusion (ICF) implosions and are essential for understanding implosion performance to constrain ICF capsule design. When fusion fuel contains Deuterium (D) and Tritium (T) gas, reaction history is informed by measuring the 16.75 MeV gamma rays generated from the D(T,γ) 5 He reaction. Such DT based reaction history measurements have not been made on the Magnetized Laser Inertial Fusion (MagLIF) platform on Sandia’s Z-Machine due to the lack of Tritium being used. The recent development of ICF implosions with tritiated fuel will open the possibility of measuring the gamma reaction history on the Z-Machine. A forward model of the Gamma Reaction History diagnostic on Z (GRH-Z) has been developed using the MCNP6.3 (Monte-Carlo N-Particle) radiation transport code. The model included the Z-Machine geometry of interest to characterize the impact of neutron induced gamma rays on the DT reaction history measurements. In addition, the impulse response functions of the GRH-Z diagnostic to understand the temporal response of the detector, and the minimum yields required to make a reaction history measurement were calculated. This approach also predicted that with T 2 gas doping of MagLIF implosions a reaction history may be made for high performance shots >8e12-2.4e13 depending on the chosen threshold for the detector, with a maximum signal to background ratio of 25%. It was found that for long duration ICF implosions that additional collimation will be needed to prevent the neutron induced gamma rays from modifying the shape of the measured DT reaction history curve.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS2014

Lessons Learned in the First Year Operating Software Defined Radios in Space

Operating three unique software defined radios (SDRs) in a space environment aboard the Space Communications and Navigation (SCaN) Testbed for over one year has provided an opportunity to gather knowledge useful for future missions considering using software defined radios. This paper provides recommendations for the development and use of SDRs, and it considers the details of each SDRs approach to software upgrades and operation. After one year, the SCaN Testbed SDRs have operated for over 1000 hours. During this time, the waveforms launched with the SDR were tested on-orbit to assure that they operated in space at the same performance level as on the ground prior to launch to obtain an initial on-orbit performance baseline. A new waveform for each SDR has been developed, implemented, uploaded to the flight system, and tested in the flight environment. Recommendations for SDR-based missions have been gathered from early development through operations. These recommendations will aid future missions to reduce the cost, schedule, and risk of operating SDRs in a space environment. This paper considers the lessons learned as they apply to SDR pre-launch checkout, purchasing space-rated hardware, flexibility in command and telemetry methods, on-orbit diagnostics, use of engineering models to aid future development, and third-party software. Each SDR implements the SCaN Testbed flight computer command and telemetry interface uniquely, allowing comparisons to be drawn. The paper discusses the lessons learned from these three unique implementations, with suggestions on the preferred approach. Also, results are presented showing that it is important to have full system performance knowledge prior to launch to establish better performance baselines in space, requiring additional test applications to be developed pre-launch. Finally, the paper presents the issues encountered with the operation and implementation of new waveforms on each SDR and proposes recommendations to avoid these issues.

radio equipment↗
NASA NTRS2014

Lessons Learned in the First Year Operating Software Defined Radios in Space

Operating three unique software defined radios (SDRs) in a space environment aboard the Space Communications and Navigation (SCaN) Testbed for over one year has provided an opportunity to gather knowledge useful for future missions considering using software defined radios. This paper provides recommendations for the development and use of SDRs, and it considers the details of each SDR's approach to software upgrades and operation. After one year, the SCaN Testbed SDRs have operated for over 1000 hours. During this time, the waveforms launched with the SDR were tested on-orbit to assure that they operated in space at the same performance level as on the ground prior to launch to obtain an initial on-orbit performance baseline. A new waveform for each SDR has been developed, implemented, uploaded to the flight system, and tested in the flight environment. Recommendations for SDR-based missions have been gathered from early development through operations. These recommendations will aid future missions to reduce the cost, schedule, and risk of operating SDRs in a space environment. This paper considers the lessons learned as they apply to SDR pre-launch checkout, purchasing space-rated hardware, flexibility in command and telemetry methods, on-orbit diagnostics, use of engineering models to aid future development, and third-party software. Each SDR implements the SCaN Testbed flight computer command and telemetry interface uniquely, allowing comparisons to be drawn. The paper discusses the lessons learned from these three unique implementations, with suggestions on the preferred approach. Also, results are presented showing that it is important to have full system performance knowledge prior to launch to establish better performance baselines in space, requiring additional test applications to be developed pre-launch. Finally, the paper presents the issues encountered with the operation and implementation of new waveforms on each SDR and proposes recommendations to avoid these issues.

space communication↗
NASA NTRS2012

The Strengths and Limitations of Satellite Data for Evaluating Tropospheric Processes in Chemistry-Climate Models

There is now a wealth of satellite data products available with which to evaluate a model fs simulation of tropospheric composition and other model processes. All of these data products have their strengths and limitations that need to be considered for this purpose. For example, uncertainties are introduced into a data product when 1) converting a slant column to a vertical column and 2) estimating the amount of a total column of a trace gas (e.g., ozone, nitrogen dioxide) that resides in the troposphere. Oftentimes, these uncertainties are not well quantified and the satellite data products are not well evaluated against in situ observations. However, these limitations do not preclude us from using these data products to evaluate our model processes if we understand these strengths and limitations when developing diagnostics. I will show several examples of how satellite data products are being used to evaluate particular model processes with a focus on the strengths and limitations of these data products. In addition, I will introduce the goals of a newly formed team to address issues on the topic of "satellite data for improved model evaluation and process studies" that is established in support of the IGAC/SPARC Global Chemistry ]Climate Modeling and Evaluation Workshop.

Duncan, Bryan↗