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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
NASA NTRS1978

A concept for a transparent data acquisition and distribution system for spaceflight applications

The paper describes the Modular Data System concept of the NASA End-to-End Data System program. Data from a single instrument along with the necessary ancillary data will be assembled into self-contained packets and subsequently transmitted over various communications links (space telemetry channel, ground communications circuits, etc.) to the experimenter's facility in real time; reliable error control coding will be included in each link transmission to protect the integrity of the data packets. A major objective is to make the entire data acquisition and distribution process transparent to the experimenter in the sense that the output terminal of the distribution system will be physically, logically and electrically identical to that of the experiment output channel.

Greene, E. P.↗
DOE OSTI2021

FedADMP: A Joint Anomaly Detection and Mobility Prediction Framework via Federated Learning

With the proliferation of mobile devices and smart cameras, detecting anomalies and predicting their mobility are critical for enhancing safety in ubiquitous computing systems. Due to data privacy regulations and limited communication bandwidth, it is infeasible to collect, transmit, and store all data from mobile devices at a central location. To overcome this challenge, we propose FedADMP, a federated learning based joint Anomaly Detection and Mobility Prediction framework. FedADMP adaptively splits the training process between the server and clients to reduce computation loads on clients. To protect the privacy of user data, clients in FedADMP upload only intermediate model parameters to the cloud server. We also develop a differential privacy method to prevent the cloud server and external attackers from inferring private information during the model upload procedure. Extensive experiments using real-world datasets show that FedADMP consistently outperforms existing methods.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1981

Light transport and general aviation aircraft icing research requirements

A short term and a long term icing research and technology program plan was drafted for NASA LeRC based on 33 separate research items. The specific items listed resulted from a comprehensive literature search, organized and assisted by a computer management file and an industry/Government agency survey. Assessment of the current facilities and icing technology was accomplished by presenting summaries of ice sensitive components and protection methods; and assessments of penalty evaluation, the experimental data base, ice accretion prediction methods, research facilities, new protection methods, ice protection requirements, and icing instrumentation. The intent of the research plan was to determine what icing research NASA LeRC must do or sponsor to ultimately provide for increased utilization and safety of light transport and general aviation aircraft.

Breeze, R. K.↗
NASA NTRS1986

Heating distribution comparison between asymmetric and symmetric blunt cones

An experiment was performed to compare the heating distribution between symmetric and asymmetric large-angle blunt cones, with cone angles of 100, 120, and 140 deg. These hot-wall data were obtained from models made from typical thermal protection insulation for proposed aeroassisted orbital transfer vehicles. Experimental data are compared with predictions using a boundary-layer integral matrix procedure with kinetics to determine how well the heating distribution over an asymmetric cone could be approximated using axisymmetric solutions for a cone and spherical segment. In addition, a relationship between the stagnation-point heat-transfer rate and the bow-shock standoff distance for these cones is discussed. The heat-distribution data from the symmetric and asymmetric cones were very similar. Numerical results compared well with the measured wall temperatures at the stagnation point but slightly underpredicted them over the conical portion of the models.

Stewart, D. A.↗
NASA NTRS2020

NASA-ISRO Synthetic Aperture Radar (NISAR) Mission

NISAR is a multi-disciplinary Earth-observing radar mission that makes global measurements of land surface changes that will greatly improve Earth system models. NISAR data will clarify spatially and temporally complex phenomena, including ecosystem disturbances, ice sheet collapse, and natural hazards including earthquakes, tsunamis, volcanoes, and landslides. It provides societally relevant data that will enable better protection of life and property. The mission, a NASA-ISRO partnership, uses two fully polarimetric SARs, one at L-band (L-SAR) and one at S-band (S-SAR), in exact repeating orbits every 12 days that allows interferometric combination of data on repeated passes. NASA provides the L SAR; a shared deployable reflector; an engineering payload that supports mission-specific data handling, navigation and communication functions; science observation planning and L SAR data processing. ISRO provides the S-SAR, spacecraft, launch vehicle, satellite operations, and S-SAR data processing. The mission will be launched from the Satish Dhawan Space Centre, Sriharikota, India. Mission development has addressed many unique challenges and incorporates many “firsts” for a jointly-developed free-flyer radar science mission.

Sarma, C V H S↗
NASA NTRS2011

Isotherm Sensor Calibration Program for Mars Science Laboratory Heat Shield Flight Data Analysis

Seven instrumented sensor plugs were installed on the Mars Science Laboratory heat shield in December 2008 as part of the Mars Science Laboratory Entry, Descent, and Landing Instrumentation (MEDLI) project. These sensor plugs contain four in-depth thermocouples and one Hollow aErothermal Ablation and Temperature (HEAT) sensor. The HEAT sensor follows the time progression of a 700 C isotherm through the thickness of a thermal protection system (TPS) material. The data can be used to infer char depth and, when analyzed in conjunction with the thermocouple data, the thermal gradient through the TPS material can also be determined. However, the uncertainty on the isotherm value is not well defined. To address this uncertainty, a team at NASA Ames Research Center is carrying out a HEAT sensor calibration test program. The scope of this test program is described, and initial results from experiments conducted in the laboratory to study the isotherm temperature of the HEAT sensor are presented. Data from the laboratory tests indicate an isotherm temperature of 720 C 60 C. An overview of near term arc jet testing is also given, including preliminary data from 30.48cm 30.48cm PICA panels instrumented with two MEDLI sensor plugs and tested in the NASA Ames Panel Test Facility. Forward work includes analysis of the arc jet test data, including an evaluation of the isotherm value based on the instant in time when it reaches a thermocouple depth.

Santos, Jose A.↗
DOE OSTI2024

Generating Emissions Inventory for Carbon Capture and Storage Analysis for Carbon-Intensive Industrial Sectors

Decarbonizing the industrial sector is critical to achieve carbon dioxide (CO2) emissions reductions goals of the Biden Administration. Currently available decarbonization options include electrification, fuel switching to zero carbon fuels like green hydrogen (H2) and carbon capture and storage (CCS). Application of post-combustion carbon capture (PCCC) technology in the power sector, as well as research at the U.S. Department of Energy's Fossil Energy and Carbon Management (FECM) Office has shown that its application in the industrial sector could have co-benefits in the form of emissions reductions of non-CO2 regulated pollutants. For example, solvent based PCCC systems require pre-conditioning of flue gas to remove sulfur and particulate matter (PM) upstream of the CO2 absorber. However, there is a lack of understanding about the type of non-CO2 pollutants which can be captured and the amount of reduction possible. PCCC application differs across industrial sectors as it depends on the availability of decarbonization options, characteristics of industrial processes and the amount and composition of pollutant flows. Certain facilities can also have multiple effluent flows with or without a CO2 stream. As such, understanding industrial processes and their effluent flows in detail is required to quantify the co-benefits opportunities presented by PCCC. Considering this requirement, the goal of this analysis is to develop a high-resolution inventory of effluent flows from facilities of 8 industrial sectors in the U.S. These industrial sectors - ethanol, ammonia, cement, steel, natural gas processing, hydrogen, petroleum refining and wood and pulp products - have carbon-intensive effluent flows, and thus are prime candidates for PCCC applications. In this study, we map the composition of pollutant flow from flue stacks across the identified facilities. Using data available in three Environmental Protection Agency (EPA) databases - the Green House Gas Reporting Program (GHGRP), the National Emissions Inventory (NEI) and the Toxic Release Inventory (TRI), we create a combined inventory which lists the type, amount, and concentration of pollutant flows. Using total weight of the pollutant flow back calculated from observed data for CO2 concentrations in flue gas for individual sectors, we calculate the concentration of each pollutant in the flue gas stream. Thus, the resultant emissions inventory includes the following details for each facility in the sector: facility-level and if possible, process-level pollutant flows, concentrations of pollutants in the flue gas, and geographical coordinates of the facilities. A detailed statistical analysis and summary allows us to search for erroneous data and remove them from the final inventory. The generation of the inventory is achieved using a python-based framework which can recreate this inventory for other industrial sectors as well as using newer releases of emission inventories from EPA. The statistical analysis performed on the inventory is also calibrated and automated to identify outliers efficiently.

air pollutants↗
DOE OSTI2020

Low Count and Background Radionuclides Analysis - 20488

The US Department of Energy (DOE) is often faced with the need to evaluate radionuclides at low concentrations. When site sample data are likely to be close to threshold activity concentrations of interest, then the means by which the radiochemical analysis is performed and reported is critical. This situation can occur when differentiating from zero (presence/absence) for radionuclides that do not occur naturally, close comparison with environmental background for naturally occurring radionuclides, close comparison with a risk- or dose-based threshold concentrations of interest, or even comparisons across studies. There are several analytical issues that are of concern, but the two that appear to cause incorrect decisions to be made most often involve establishing detection limits and subtracting ambient background conditions in the laboratory. These issues are not critical when radionuclide activity concentrations are large relative to thresholds of concern, but they seem to be poorly understood when it matters. When the comparisons are important and are likely to be close to a threshold of interest, then the general contract with the analytical laboratories needs to be changed so that the right or appropriate data are obtained. The concern is that important decisions are made incorrectly more often as greater scrutiny is placed on DoE's radionuclide cleanup or monitoring decisions by the public and other stakeholders. Examples are presented of problems that have been observed for different projects, both within and outside the realm of DOE and NRC remediation and radioactive waste disposal problems, and solutions are offered that should lead to better data from which important decisions need to be made. The first example is from Los Alamos National Laboratory (LANL) and involves radionuclide concentrations in soil and rock beneath LANL's Material Disposal Area (MDA) G. An initial review of the data led to a conclusion that americium and plutonium are a long way present beneath MDA G. A more thorough review of the data that accounted properly for ambient background and the detection limits that had been established led to the opposite conclusion. Another example is from the Nevada National Security Site where tritium results from one of the wells were unexpectedly high. Proper understanding and analysis of ambient background led to the conclusion that the increased concentrations were not so obvious, and that a different contract with the analytical laboratory was needed to provide more appropriate data to support a better determination. Other examples are used from regulatory review of projects in Nevada, where background levels and secular equilibrium for naturally occurring radionuclides are not established correctly because of analytical issues. The same basic issues have also been found to create difficulties analyzing historical data from the West Valley Demonstration Project. There is evidence in the data that the apparent lack of secular equilibrium where it is expected to exist is related to ambient background subtraction or other analytical issues. A final example is presented for analysis of Tc-99 in samples of depleted uranium. In this case, two different studies that were performed only three months apart provide quite different results. The US Environmental Protection Agency (EPA) established the data quality objectives (DQO) process in the mid-1980's to establish decision performance criteria for data collection. EPA guidance (EPA G-4, for example) clearly distinguishes between DQOs and measurement performance objectives (MQOs) that should be addressed for laboratory analysis of samples. The language of DQOs and MQOs has become confused over time it seems, and the subsequent effects seem to include a lack of attention to decision performance and a routine approach to measurement quality. In order to better address radionuclide sample analysis when the concentrations are close to thresholds of concern, which might be zero for some radionuclides, background for others, and risk-based thresholds for yet others, it is important that routine laboratory analysis methods are adjusted, and that the project team and the laboratory work closely together to ensure that the data meets the MQO requirements of laboratory analysis and reporting of results, and that the MQOs effectively support project-specific DQOs. This basic approach will be applied in Los Alamos in the coming year to the collection of moisture data from underneath MDA T that will be analyzed for americium and neptunium isotopes. Proper understanding of the radiochemistry methods and reporting, and of appropriate statistical methods is critical to the success of such projects, ensuring that the right decisions are made. (authors)

07 ISOTOPE AND RADIATION SOURCES↗
NASA NTRS2015

Mars2020 Entry, Descent, and Landing Instrumentation (MEDLI2): Science Objectives and Instrument Requirements

NASAs exploration and technology roadmaps call for capability advancements in Mars entry, descent, and landing (EDL) systems to enable increased landed mass, a higher landing precision, and a wider planetary access. It is also recognized that these ambitious EDL performance goals must be met while maintaining a low mission risk in order to pave the way for future human missions. As NASA is engaged in developing new EDL systems and technologies via testing at Earth, instrumentation of existing Mars missions is providing valuable engineering data for performance improvement, risk reduction, and an improved definition of entry loads and environment. The most notable recent example is the Mars Entry, Descent and Landing Instrument (MEDLI) suite hosted by Mars Science Laboratory for its entry in Aug 2012. The MEDLI suite provided a comprehensive dataset for Mars entry aerodynamics, aerothermodynamics and thermal protection system (TPS) performance. MEDLI data has since been used for unprecedented reconstruction of aerodynamic drag, vehicle attitude, in-situ atmospheric density, aerothermal heating, and transition to turbulence, in-depth TPS performance and TPS ablation. [1,2] In addition to validating predictive models, MEDLI data has demonstrated extra margin available in the MSL forebody TPS, which can potentially be used to reduce vehicle parasitic mass. The presentation will introduce a follow-on MEDLI instrumentation suite (called MEDLI2) that is being developed for Mars-2020 mission. MEDLI2 has an enhanced scope that includes backshell instrumentation, a wider forebody coverage, and instruments that specifically target supersonic aerodynamics. Similar to MEDLI, MEDLI2 uses thermal plugs with embedded thermocouples and ports through the TPS to measure surface pressure. MEDLI2, however, also includes heat flux sensors in the backshell and a low range pressure transducer to measure afterbody pressure.

Aerothermodynamics↗
NASA NTRS2023

Pacific Northwest Health & Air Quality: Monitoring Trends in Air Quality During a Drought Case Study to Improve Public Health Response to Drought Threats

Recent studies have documented a correlation between air quality and drought in the United States, which has been linked with increased aerosols including airborne particulate matter (PM) during drought conditions. This study partnered with local health departments to evaluate trends in air quality in the Pacific Northwest during the evolution of drought conditions using aerosol optical depth (AOD) observations collected by NASA’s Moderate Resolution Imaging Spectroradiometer (MODIS) sensor aboard the Terra and Aqua satellites. These satellite data were analyzed in conjunction with ground-based PM2.5 and PM10 data sourced from the Environmental Protection Agency (EPA)’s network of ground-based monitors and the Standardized Precipitation Evapotranspiration Index (SPEI) drought index. Based on recommendations by local health departments, this study examined air quality trends between 2015 and 2022 in 12 counties within Oregon and Washington that reflected diversity in population density, drought exposure, rural and urban status, and data availability from EPA monitors. Overall, results indicated variation in relationships among drought, satellite, and ground-based air quality data across the study area. This study did not control for the impact of wildfire events on air quality and also did not investigate shorter SPEI aggregation periods, both of which are avenues for future research. This project supplemented research into links between drought and human health and provided health departments with an objective foundation from which they can communicate public health risks to local communities.

Abby Sgan↗
NASA NTRSDate not supplied

Monitoring Trends in Air Quality During a Drought: Case Study to Improve Public Health Response to Drought Threats

Drought has been an area of distinct concern in the Pacific Northwest since the mid-2010s. Recent studies have documented a correlation between air quality and drought in the United States, which is often observed in increased aerosols including airborne particulate matter (PM). This study partnered with the Oregon Health Authority and Washington State Department of Health to evaluate trends in air quality in the Pacific Northwest during the evolution of drought conditions using aerosol optical depth (AOD) observations collected by NASA’s Moderate Resolution Imaging Spectroradiometer (MODIS) sensor aboard the Terra and Aqua satellites. These satellite data were analyzed in conjunction with ground-based PM2.5 and PM10 data sourced from the Environmental Protection Agency (EPA) Air Quality System’s network of ground-based monitors and the Standardized Precipitation Evapotranspiration Index drought index. Based on recommendations by local health departments, this study examined air quality trends between 2015 and 2022 in 12 counties within Oregon and Washington that reflected diversity in population density, drought exposure, rural and urban status, and data availability from EPA AQS monitors. The findings from this study provided supplemental information to the ongoing efforts by community health stakeholders to study the public health impacts of drought and support public health responses to future drought events.

Taylor West↗
DOE OSTI2021

Model fusion with physics-guided machine learning: Projection-based reduced-order modeling

The unprecedented amount of data generated from experiments, field observations, and large-scale numerical simulations at a wide range of spatiotemporal scales has enabled the rapid advancement of data-driven and especially deep learning models in the field of fluid mechanics. Although these methods are proven successful for many applications, there is a grand challenge of improving their generalizability. This is particularly essential when data-driven models are employed within outer-loop applications like optimization. In this work, we put forth a physics-guided machine learning (PGML) framework that leverages the interpretable physics-based model with a deep learning model. Leveraging a concatenated neural network design from multi-modal data sources, the PGML framework is capable of enhancing the generalizability of data-driven models and effectively protects against or inform about the inaccurate predictions resulting from extrapolation. We apply the PGML framework as a novel model fusion approach combining the physics-based Galerkin projection model and long- to short-term memory (LSTM) network for parametric model order reduction of fluid flows. We demonstrate the improved generalizability of the PGML framework against a purely data-driven approach through the injection of physics features into intermediate LSTM layers. Our quantitative analysis shows that the overall model uncertainty can be reduced through the PGML approach, especially for test data coming from a distribution different than the training data. Moreover, we demonstrate that our approach can be used as an inverse diagnostic tool providing a confidence score associated with models and observations. The proposed framework also allows for multi-fidelity computing by making use of low-fidelity models in the online deployment of quantified data-driven models.

42 ENGINEERING↗
NASA NTRS2004

Comparison of Satellite Observations of Aerosol Optical Depth to Surface Monitor Fine Particle Concentration

Under NASA's Earth Science Applications Program, the Infusing satellite Data into Environmental Applications (IDEA) project examined the relationship between satellite observations and surface monitors of air pollutants to facilitate a more capable and integrated observing network. This report provides a comparison of satellite aerosol optical depth to surface monitor fine particle concentration observations for the month of September 2003 at more than 300 individual locations in the continental US. During September 2003, IDEA provided prototype, near real-time data-fusion products to the Environmental Protection Agency (EPA) directed toward improving the accuracy of EPA s next-day Air Quality Index (AQI) forecasts. Researchers from NASA Langley Research Center and EPA used data from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument combined with EPA ground network data to create a NASA-data-enhanced Forecast Tool. Air quality forecasters used this tool to prepare their forecasts of particle pollution, or particulate matter less than 2.5 microns in diameter (PM2.5), for the next-day AQI. The archived data provide a rich resource for further studies and analysis. The IDEA project uses data sets and models developed for tropospheric chemistry research to assist federal, state, and local agencies in making decisions concerning air quality management to protect public health.

Kleb, Mary M.↗
NASA NTRS2021

Evidence for the Protection of N-heterocycles from Gamma Radiation by Mars Analogue Minerals

Organic compounds have been delivered to the surface of Mars via meteorites, comets and interplanetary dust particles for billions of years. Determining the effects of high energy radiation and galactic cosmic radiation (GCR) on these organic compounds is critical for understanding the potential for the preservation of organic molecules associated with past or present life, and where to look for possible chemical bio- signatures during future Mars missions. Understanding how these effects are attenuated by the mineral matrix and the depth at which they are buried have been challenging to determine in situ on Mars. There have been very few experimental studies on the survival of organic compounds under radiation from a gamma source under realistic conditions, and their interpretation until now has been difficult due to the lack of data for actual radiation levels on Mars. Using the in-situ data obtained by the MSL/RAD instrument to anchor the dose calculations, here we show that the N-heterocycles purine and uracil, crucial components of biochemical processes in extant living systems, mixed with calcite, anhydrite, and kaolinite as Mars analogue minerals can survive the effects of radiation with a dose corresponding to ~500,000 years on the Martian surface. The extent of survival varied not only with the nature of the organic compound, but its depth from the surface. These results provide new experimental data for the degree of protection offered by the regolith, in conjunction with minerals, for organic compounds that may be present on Mars.

mars↗
NASA NTRS2009

Ultra-high Temperature Emittance Measurements for Space and Missile Applications

Advanced modeling and design efforts for many aerospace components require high temperature emittance data. Applications requiring emittance data include propulsion systems, radiators, aeroshells, heatshields/thermal protection systems, and leading edge surfaces. The objective of this work is to provide emittance data at ultra-high temperatures. MSFC has a new instrument for the measurement of emittance at ultra-high temperatures, the Ultra-High Temperature Emissometer System (Ultra-HITEMS). AZ Technology Inc. developed the instrument, designed to provide emittance measurements over the temperature range 700-3500K. The Ultra-HITEMS instrument measures the emittance of samples, heated by lasers, in vacuum, using a blackbody source and a Fourier Transform Spectrometer. Detectors in a Nicolet 6700 FT-IR spectrometer measure emittance over the spectral range of 0.4-25 microns. Emitted energy from the specimen and output from a Mikron M390S blackbody source at the same temperature with matched collection geometry are measured. Integrating emittance over the spectral range yields the total emittance. The ratio provides a direct measure of total hemispherical emittance. Samples are heated using lasers. Optical pyrometry provides temperature data. Optical filters prevent interference from the heating lasers. Data for Inconel 718 show excellent agreement with results from literature and ASTM 835. Measurements taken from levitated spherical specimens provide total hemispherical emittance data; measurements taken from flat specimens mounted in the chamber provide near-normal emittance data. Data from selected characterization studies will be presented. The Ultra-HITEMS technique could advance space and missile technologies by advancing the knowledge base and the technology readiness level for ultra-high temperature materials.

Rogers, Jan↗
DOE OSTI2024

Electrical Fault and Power Quality Detection Algorithms and Customer-Owned DERs Monitoring with a Cyber Grid Guard System and DLT

In this study, the electrical fault and power quality detection algorithms and customer-owned DERs monitoring use cases were implemented, with a Cyber Grid Guard system and DLT. Electrical utilities continue to deploy more intelligent electronic devices (IEDs) inside and outside electrical substations, and are associated with customer-owned distributed energy resources (DERs). Data from these IEDs, such as power meters and protection relays, must be kept confidential and of high integrity. Blockchain technology has the potential to increase microgrid resilience by enhancing data sharing security. The growing use of IEDs and customer-owned renewable energy sources (DERs) may make it necessary to connect Distributed Ledger Technology (DLT) with power system applications. We implemented the electrical faulted phase detection and power quality monitoring algorithms with a Cyber Grid Guard (CGG) system using DLT. In addition, the DERs (wind turbine farms) use case and protective relay cyber-event tests were assessed, by using the CGG system with DLT. In the experimental model, the testbed was created by using a real-time simulator and CGG system with power meters/ protective relays in the loop. The data collected from the CGG system and IEDs were compared with the same time stamp source. These results showed the successful assessment of protection, control and monitoring applications using a CGG system with DLT. In the future, power system applications for the ESGT with DERs and the CGG system will be based on executing smart contracts between electrical utilities and customer-owned DERs.

Piesciorovsky, Emilio↗
DOE OSTI2024

Integrating AEAD Ciphers into Software-Defined-Storage Systems

The use of software-defined storage (SDS) systems to store sensitive data is becoming increasingly prevalent. However, these systems primarily implement security measures to ensure the confidentiality and availability of stored data, with limited consideration for the protection of its integrity. This paper outlines why this is a harmful development, as well as how integrity-protecting measures can be included into SDS systems. To demonstrate the practical challenges and opportunities of such measures, we integrated "authenticated encryption with associated data" (AEAD) ciphers into the widely used SDS system Ceph, specifically, into its block storage interface, to secure the integrity of stored data and metadata. Ultimately, we identify the characteristics that an SDS system should possess to adopt our methodology.

Mohren, David [University of New Brunswick, Canada↗
NASA NTRS2019

Heat-Cleaned Nextel in MMOD Shielding

Meteoroid and orbital debris (MMOD) shielding can include NextelTM ceramic cloth in the outer layers of the shielding to enhance MMOD breakup. The Nextel fabric can contain size (or sizing) which aids in manufacture of the fabric. Sizing is a starch, oil or waxy material that is added to the rovings and yarns to protect the fibers from being cut or broken during the fabric manufacturing process and by later handling. For spacecraft applications, sizing is removed by heat-cleaning to reduce/eliminate off-gassing during vacuum operations. After the sizing is removed, the fibers in the woven fabric are prone to breakage during handling which reduces fabric strength. Because heat-cleaned Nextel tends to shed fibers that can be irritating to workers, the usual practice for hypervelocity impact tests is to use Nextel with sizing. The reduced strength of heat-cleaned Nextel does not typically effect the performance of MMOD shields with Nextel used in outer layers of the shield, because the density and areal density of the ceramic fibers in the fabric control MMOD breakup (not fabric strength). This paper provides data demonstrating that hypervelocity impact protection performance is not adversely altered for shields containing heat-cleaned Nextel compared to Nextel with sizing.

Christiansen, Eric L.↗