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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 NTRS1997

Extreme Ultraviolet Imaging Telescope (EIT)

Efforts concentrated on development and implementation of the SolarSoft (SSW) data analysis system. From an EIT analysis perspective, this system was designed to facilitate efficient reuse and conversion of software developed for Yohkoh/SXT and to take advantage of a large existing body of software developed by the SDAC, Yohkoh, and SOHO instrument teams. Another strong motivation for this system was to provide an EIT analysis environment which permits coordinated analysis of EIT data in conjunction with data from important supporting instruments, including Yohkoh/SXT and the other SOHO coronal instruments; CDS, SUMER, and LASCO. In addition, the SSW system will support coordinated EIT/TRACE analysis (by design) when TRACE data is available; TRACE launch is currently planned for March 1998. Working with Jeff Newmark, the Chianti software package (K.P. Dere et al) and UV /EUV data base was fully integrated into the SSW system to facilitate EIT temperature and emission analysis.

Lemen, J. R.↗
NASA NTRS2006

Spitzer Observatory Operations -- Increasing Efficiency in Mission Operations

This paper explores the how's and why's of the Spitzer Mission Operations System's (MOS) success, efficiency, and affordability in comparison to other observatory-class missions. MOS exploits today's flight, ground, and operations capabilities, embraces automation, and balances both risk and cost. With operational efficiency as the primary goal, MOS maintains a strong control process by translating lessons learned into efficiency improvements, thereby enabling the MOS processes, teams, and procedures to rapidly evolve from concept (through thorough validation) into in-flight implementation. Operational teaming, planning, and execution are designed to enable re-use. Mission changes, unforeseen events, and continuous improvement have often times forced us to learn to fly anew. Collaborative spacecraft operations and remote science and instrument teams have become well integrated, and worked together to improve and optimize each human, machine, and software-system element.

operational efficiency↗
NASA NTRS2010

Cassini Titan Science Integration: Getting a 'Jumpstart' on the Process

The Cassini spacecraft has been in orbit for five years, returning a wealth of scientific data from Titan and the Saturn system. The mission is a cooperative undertaking between NASA, ESA and the Italian Space Agency and the project is currently planning for a second extension of the mission. The Cassini Solstice Mission (CSM) will extend the mission's lifetime until Saturn's northern summer solstice in 2017. The Titan Orbiter Science Team (TOST) has the task of integrating the science observations for all 126 targeted Titan flybys (44 in the Prime Mission, 26 in the first extension (Equinox Mission), and 56 in the second extension (Solstice Mission)) contained in the chosen trajectory. Cassini science instruments are body-fixed with limited ability to articulate; thus, the spacecraft pointing during the flybys must be allocated among the instruments to accomplish the mission's science goals. The science that can be accomplished on each Titan flyby also critically depends on the closest approach altitude, which is in turn determined by the attitude, but changing the altitude impacts the overall trajectory for the Solstice Mission. During the Prime and Extended missions, TOST has learned that the best way to achieve Cassini's Titan science goals is via a 'jumpstart' process prior to final delivery of the trajectory. The jumpstart is driven by the desire to balance Titan science across the entire set of flybys during the CSM, and to influence any changes (tweaks) to the flyby altitudes. By the end of the jumpstart, TOST produces Master Timelines for each flyby, identifying each flyby's prime science observations and allocating control of the spacecraft attitude to specific instrument teams. In addition, developing timelines early, while the science and operations teams are still fully funded, decreases the future workload in integration and implementation.

Steadman, Kimberly B.↗
NASA NTRS2001

What is the Relationship Between Heavy Ion Outflow and High-Latitude Energetic Precipitation?

Second quarter progress report for year 3 on contract NASW-99002 "What is the Relationship between heavy ion outflow and high latitude energetic particle precipitation". In this Project we are studying the relationship between the fluxes, mean energies, and field-aligned flow speeds of escaping suprathermal H+ and 0+ measured by the TEAMS instrument on FAST and the energy flux of precipitating electrons obtained from the LBHL images taken by the UVI camera on POLAR. In this portion of the project we are using UVI images to tell us when substorm onsets occur and how the auroral zone changes during the course of a substorm. We are correlating this information with TEAMS flux measurements made over the auroral zone at times close to these substorms. The goal is to understand how the flux of suprathermal ion outflow varies with substorm phase.

Wilson, Gordon R.↗
NASA NTRS2018

Results from ORACLES-2016: Observed Biomass Burning Aerosol Properties over the Southeast Atlantic Ocean and the Relationship to Meteorology

The Southeast Atlantic Ocean (SEA), with seasonal biomass burning (BB) smoke plumes overlying persistent stratocumulus cloud deck, offers an excellent natural laboratory to make the observations necessary to understand the complexities of aerosol-cloud-radiation interactions. The first field deployment of the NASA ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) campaign was conducted in September of 2016 out of Walvis Bay, Namibia. During this deployment, two NASA aircraft (a P-3 and an ER-2) were flown with a suite of aerosol, cloud, radiation, and meteorological instruments for remote-sensing and in-situ observations. In this talk, I will first present results from an intercomparison of the different instrument retrievals for the 2016 flights, with a specific focus on the measures of aerosol absorption. In ORACLES, data collected by eight different instrument teams are used to derive aerosol properties over this region by independent methods. We focus on the single scattering albedo (SSA), a measure of the relative absorption versus total extinction by aerosols, as the main comparable property between all methods. I will also discuss comparisons of the retrieved aerosol absorption parameters, as well as the agreement and the variability seen between different instruments, and spatially over the study region. Another important factor in understanding aerosol radiative effects is how the magnitude of these effects may be modified by meteorological conditions. I will next describe observations collected from the P-3 aircraft (from near-surface up to 6-7 kilometers) which show a strong correlation between the in-situ pollution indicators (carbon monoxide and aerosol properties) and atmospheric water vapor content, seen at all altitudes above the boundary layer. This condition is seen to persist over all flights, with minimal detrainment during advection from the continental source. In exploring the potential causal factors behind and implications of this relationship, we see indications that convective dynamics over the continent likely contribute to this elevated signal, but neither meteorological reanalysis nor trajectory analysis fully capture the magnitude and vertical structure of the observed elevated signal. Finally, I will discuss the radiative implications of the observed correlations, a topic of ongoing analysis in ORACLES: understanding the mechanisms which cause water vapor to covary with plume strength is important to quantifying the radiative effects (direct and semi-direct) of biomass burning aerosol in the region.

Pistone, Kristina↗
DOE OSTI2022

New Optical Designs for Radiation Imaging Systems [Slides]

Presentation to be presented during the first annual Prompt Radiation Detection and Imaging Workshop, hosted by the NNSS Dynamic Instruments Team, April 25–28, 2022, at NLV C-01 Auditorium and via Webex.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS2012

From EXOSAT to the High Energy Astrophysics Science Archive (HEASARC): X-ray Astronomy Comes of Age

In May 1983 the European Space Agency launched EXOSAT, its first X-ray astronomy observatory. Even though it lasted only 3 short years, this mission brought not only new capabilities that resulted in unexpected discoveries, but also a pioneering approach to operations and archiving that changed X-ray astronomy from observations led by small instrument teams, to an observatory approach open to the entire community through a guest observer program. The community use of the observatory was supported by a small dedicated team of scientists, the precursor to the data center activities created to support e.g. Chandra and XMM-Newton. The new science capabilities of EX OS AT included a 90 hr highly eccentric high earth orbit that allow unprecedented continuous coverage of sources as well as direct communication with the satellite that allowed real time decisions to respond to unexpected events through targets of opportunity. The advantages of this orbit demonstrated by EXOSAT resulted in Chandra and XMM-Newton selecting similar orbits. The three instruments on board the EXOSAT observatory were complementary, designed to give complete coverage over a wide energy band pass of 0.05-50 keY. An onboard processor could be programmed to give multiple data modes that could be optimized in response to science discoveries: These new capabilities resulted in many new discoveries including the first comprehensive study of AGN variability, new orbital periods in X-ray binaries and cataclysmic variables, new black holes, quasi-periodic oscillations from neutron stars and black holes and broad band X-ray spectroscopy. The EXOSAT team generated a well-organized database accessible worldwide over the nascent internet, allowing remote selection of data products, making samples and undertaking surveys from the data. The HEASARC was established by NASA at Goddard Space Flight Center in 1990 as the repository of NASA X-ray and Gamma-ray data. The proven EXOSAT database system became the core of the HEASARC infrastructure. The HEASARC pioneered many concepts now taken for granted including standardized formats using FITS files, restoring data from earlier missions, multi-mission analysis tools and a searchable archive over the world wide web.

White, Nicholas E.↗
NASA NTRS2015

Magnetospheric Multiscale Instrument Suite Operations and Data System

The four Magnetospheric Multiscale (MMS) spacecraft will collect a combined volume of approximately 100 gigabits per day of particle and field data. On average, only 4 gigabits of that volume can be transmitted to the ground. To maximize the scientific value of each transmitted data segment, MMS has developed the Science Operations Center (SOC) to manage science operations, instrument operations, and selection, downlink, distribution, and archiving of MMS science data sets. The SOC is managed by the Laboratory for Atmospheric and Space Physics (LASP) in Boulder, Colorado and serves as the primary point of contact for community participation in the mission. MMS instrument teams conduct their operations through the SOC, and utilize the SOC's Science Data Center (SOC) for data management and distribution. The SOC provides a single mission data archive for the housekeeping and science data, calibration data, ephemerides, attitude and other ancillary data needed to support the scientific use and interpretation. All levels of data products will reside at and be publicly disseminated from the SDC. Documentation and metadata describing data products, algorithms, instrument calibrations, validation, and data quality will be provided. Arguably, the most important innovation developed by the SOC is the MMS burst data management and selection system. With nested automation and 'Scientist-in-the-Loop' (SITL) processes, these systems are designed to maximize the value of the burst data by prioritizing the data segments selected for transmission to the ground. This paper describes the MMS science operations approach, processes and data systems, including the burst system and the SITL concept.

Baker, D. N.↗
NASA NTRS2014

Handling Late Changes to Titan Science

The Cassini mission has been in orbit for eight years, returning a wealth of scientific data from Titan and the Saturnian system. The mission, a cooperative undertaking between NASA, ESA and ASI, is currently in its second extension of the prime mission. The Cassini Solstice Mission (CSM) extends the mission's lifetime until Saturn's northern summer solstice in 2017. The Titan Orbital Science Team (TOST) has the task of integrating the science observations for all 56 targeted Titan flybys in the CSM. In order to balance Titan science across the entire set of flybys during the CSM, to optimize and influence the Titan flyby altitudes, and to decrease the future workload, TOST went through a "jumpstart" process before the start of the CSM. The "jumpstart" produced Master Timelines for each flyby, identifying prime science observations and allocating control of the spacecraft attitude to specific instrument teams. Three years after completing this long-range plan, TOST now faces a new challenge: incorporating changes into the Titan Science Plan without undoing the balance achieved during the jumpstart.

Pitesky, Jo Eliza↗
NASA NTRS1996

Planetary Atmosphere Dynamics and Radiative Transfer

This research program has dealt with two projects in the field of planetary atmosphere dynamics and radiative energy transfer, one theoretical and one experimental. The first project, in radiative energy transfer, incorporated the capability to isolate and quantify the contribution of individual atmospheric components to the Venus radiative balance and thermal structure to greatly improve the current understanding of the radiative processes occurring within the Venus atmosphere. This is possible by varying the mixing ratios of each gas species, and the location, number density and aerosol size distributions of the clouds. This project was a continuation of the work initiated under a 1992 University Consortium Agreement. Under the just completed grant, work has continued on the use of a convolution-based algorithm that provided the capability to calculate the k coefficients of a gas mixture at different temperatures, pressures and spectral intervals from the separate k-distributions of the individual gas species. The second primary goal of this research dealt with the Doppler wind retrieval for the Successful Galileo Jupiter probe mission in December, 1995. In anticipation of the arrival of Galileo at Jupiter, software development continued to read the radioscience and probe/orbiter trajectory data provided by the Galileo project and required for Jupiter zonal wind measurements. Sample experiment radioscience data records and probe/orbiter trajectory data files provided by the Galileo Radioscience and Navigation teams at the Jet Propulsion Laboratory, respectively, were used for the first phase of the software development. The software to read the necessary data records was completed in 1995. The procedure by which the wind retrieval takes place begins with initial consistency checks of the raw data, preliminary data reductions, wind recoveries, iterative reconstruction of the probe descent profile, and refined wind recoveries. At each stage of the wind recovery consistency is checked and maintained between the orbiter navigational data, the radioscience data, and the probe descent profile derived by the Atmospheric Instrument Team. Preliminary results show that the zonal winds at Jupiter increase with depth to approximately 150 m/s.

Atkinson, David H.↗
NASA NTRSDate not supplied

Mars Commercial-Compatible Initial Human-Precursor Surveying and Instrument-Deployment Concepts

Water is a critical resource need for future human exploration and habitation of Mars and other planetary environments. An integral scientific question in the search for life outside of Earth is: What are the constraints on life in planetary environments? One of the most critical features of habitable environments is the availability of water - both as an environment for prebiotic chemistry, abiogenesis, and life; and as a vehicle for generating geo- and electro- chemical systems that can support metabolism. Seeking evidence of life prior to human arrival is important both to preserve signs of any existing or past evidence of Martian life, reducing the risks of unintentional forward contamination of Martian environments, and to potentially protect the health of any human crews. Looking forward towards Mars, future human exploration will require a rapid, but thorough, initial survey of any local “area of operations” on Mars to determine the spatial distribution, quantity, and quality (e.g., salt/mineral/organic content) of any local water, as well as to evaluate any signs of current or extinct life. We will discuss several candidate field survey methodologies, involving humans, a teamed instrument platform and a surveying/sampling rover. These are proposed to be validated in a given terrestrial Mars analog environment exhibiting varying distributions of water (ice, permafrost, rock-bound) to evaluate the constraints on life. Commercial space exploration brings the future possibility of unprecedented mass, power and in situ instrument capability, potentially enabling thorough exploration of the geology, hydrology and astrobiology of a km-radius study-zone around a future Mars human/commercial space landing site. We propose to study several representative planetary surface precursor-survey architectures and mission concepts (that are commercial-Mars-compatible), and to test and compare them in field application. We will examine some of the performance issues, using given metrics and controls, of spacesuited humans using handheld and standalone instruments, vs. a robotic human-tended rover/drill, robot arm and instruments. The latter rover-based architecture can in turn be viewed in terms of returned-to-base sample in-situ analyses vs sample analysis performed on a standalone instrument platform deployed away from the primary area of operations.

astrobiology↗
NASA NTRS2004

The Chesapeake Lighthouse and Aircraft Measurements for Satellites (CLAMS) Experiment

NASA has developed an Earth Observing System (EOS) consisting of a series of satellites designed to study global change from space. The EOS flagship is the EOS TERRA satellite, launched in December 1999, equipped with five unique sensors to monitor and study the Earth s heat budget and many of the key controlling variables governing the Earth's climate system. CLAMS, the Chesapeake Lighthouse and Aircraft Measurements for Satellites field campaign was conducted from NASA Wallops Flight Facility and successfully executed over the middle Atlantic eastern seaboard from July 10 August 2, 2001. CLAMS is primarily a shortwave closure experiment designed to validate and improve EOS TERRA satellite data products being derived from three sensors: CERES (Clouds and Earth's Radiant Energy System), MISR (Multi-angle Imaging Spectro-Radiometer) and MODIS (MODerate Resolution Imaging Spectroradiometer). CLAMS is jointly sponsored by the CERES, MISR and MODIS instrument teams and the NASA GEWEX Global Aerosol Climatology Project (GACP). CLAMS primary objectives are to validate satellite-based retrievals of aerosol properties and vertical profiles of radiative flux, temperature and water vapor. Central to CLAMS measurement strategy is the Chesapeake Lighthouse, a stable sea platform located in the Atlantic Ocean, 13 miles east of Virginia Beach near the mouth of the Chesapeake Bay and the site of an ongoing CERES Ocean Validation Experiment (COVE). Six research aircraft were deployed to make detailed measurements of the atmosphere and ocean surface in the vicinity of COVE, over the surrounding ocean, over nearby NOAA buoys and over a few land sites. The measurements are used to validate and provide ground truth for simultaneous products being derived from TERRA data, a key step toward an improved understanding and ability to predict changes in the Earth's climate. One of the two CERES instruments on-board TERRA was programmed for Rotating Azimuth Plane Scans (RAPS) during CLAMS, increasing the CERES coverage over COVE by a factor of 10. Nine coordinated aircraft missions and numerous additional sorties were flown under a variety of atmospheric conditions and aerosol loadings. On one golden day, July 17, all six aircraft flew coordinated patterns, vertically stacked between 100 ft and 65,000 ft over the COVE site as the TERRA satellite orbited overhead. A summary of CLAMS measurement campaign and a description of the platforms and measurements is given.

Smith, William L., Jr.↗
NASA NTRS2005

Team X Spacecraft Instrument Database Consolidation

In the past decade, many changes have been made to Team X's process of designing each spacecraft, with the purpose of making the overall procedure more efficient over time. One such improvement is the use of information databases from previous missions, designs, and research. By referring to these databases, members of the design team can locate relevant instrument data and significantly reduce the total time they spend on each design. The files in these databases were stored in several different formats with various levels of accuracy. During the past 2 months, efforts have been made in an attempt to combine and organize these files. The main focus was in the Instruments department, where spacecraft subsystems are designed based on mission measurement requirements. A common database was developed for all instrument parameters using Microsoft Excel to minimize the time and confusion experienced when searching through files stored in several different formats and locations. By making this collection of information more organized, the files within them have become more easily searchable. Additionally, the new Excel database offers the option of importing its contents into a more efficient database management system in the future. This potential for expansion enables the database to grow and acquire more search features as needed.

Wallenstein, Kelly A.↗
NASA NTRS2018

GMI-IPS: Python Processing Software for Aircraft Campaigns

NASA's Atmospheric Tomography Mission (ATom) seeks to understand the impact of anthropogenic air pollution on gases in the Earth's atmosphere. Four flight campaigns are being deployed on a seasonal basis to establish a continuous global-scale data set intended to improve the representation of chemically reactive gases in global atmospheric chemistry models. The Global Modeling Initiative (GMI), is creating chemical transport simulations on a global scale for each of the ATom flight campaigns. To meet the computational demands required to translate the GMI simulation data to grids associated with the flights from the ATom campaigns, the GMI ICARTT Processing Software (GMI-IPS) has been developed and is providing key functionality for data processing and analysis in this ongoing effort. The GMI-IPS is written in Python and provides computational kernels for data interpolation and visualization tasks on GMI simulation data. A key feature of the GMI-IPS, is its ability to read ICARTT files, a text-based file format for airborne instrument data, and extract the required flight information that defines regional and temporal grid parameters associated with an ATom flight. Perhaps most importantly, the GMI-IPS creates ICARTT files containing GMI simulated data, which are used in collaboration with ATom instrument teams and other modeling groups. The initial main task of the GMI-IPS is to interpolate GMI model data to the finer temporal resolution (1-10 seconds) of a given flight. The model data includes basic fields such as temperature and pressure, but the main focus of this effort is to provide species concentrations of chemical gases for ATom flights. The software, which uses parallel computation techniques for data intensive tasks, linearly interpolates each of the model fields to the time resolution of the flight. The temporally interpolated data is then saved to disk, and is used to create additional derived quantities. In order to translate the GMI model data to the spatial grid of the flight path as defined by the pressure, latitude, and longitude points at each flight time record, a weighted average is then calculated from the nearest neighbors in two dimensions (latitude, longitude). Using SciPya's Regular Grid Interpolator, interpolation functions are generated for the GMI model grid and the calculated weighted averages. The flight path points are then extracted from the ATom ICARTT instrument file, and are sent to the multi-dimensional interpolating functions to generate GMI field quantities along the spatial path of the flight. The interpolated field quantities are then written to a ICARTT data file, which is stored for further manipulation. The GMI-IPS is aware of a generic ATom ICARTT header format, containing basic information for all flight campaigns. The GMI-IPS includes logic to edit metadata for the derived field quantities, as well as modify the generic header data such as processing dates and associated instrument files. The ICARTT interpolated data is then appended to the modified header data, and the ICARTT processing is complete for the given flight and ready for collaboration. The output ICARTT data adheres to the ICARTT file format standards V1.1. The visualization component of the GMI-IPS uses Matplotlib extensively and has several functions ranging in complexity. First, it creates a model background curtain for the flight (time versus model eta levels) with the interpolated flight data superimposed on the curtain. Secondly, it creates a time-series plot of the interpolated flight data. Lastly, the visualization component creates averaged 2D model slices (longitude versus latitude) with overlaid flight track circles at key pressure levels. The GMI-IPS consists of a handful of classes and supporting functionality that have been generalized to be compatible with any ICARTT file that adheres to the base class definition. The base class represents a generic ICARTT entry, only defining a single time entry and 3D spatial positioning parameters. Other classes inherit from this base class; several classes for input ICARTT instrument files, which contain the necessary flight positioning information as a basis for data processing, as well as other classes for output ICARTT files, which contain the interpolated model data. Utility classes provide functionality for routine procedures such as: comparing field names among ICARTT files, reading ICARTT entries from a data file and storing them in data structures, and returning a reduced spatial grid based on a collection of ICARTT entries. Although the GMI-IPS is compatible with GMI model data, it can be adapted with reasonable effort for any simulation that creates Hierarchical Data Format (HDF) files. The same can be said of its adaptability to ICARTT files outside of the context of the ATom mission. The GMI-IPS contains just under 30,000 lines of code, eight classes, and a dozen drivers and utility programs. It is maintained with GIT source code management and has been used to deliver processed GMI model data for the ATom campaigns that have taken place to date.

Damon, M. R.↗
NASA NTRSDate not supplied

Snow Depth from AMSR-2 Using Multispectral Satellite Data in an Artificial Neural Network

By using diffusion theory and Monte Carlo lidar radiative transfer simulations, Hu et al. (2022b) has derived snow depth from the first-, second- and third-order moments of the lidar backscattering pathlength distribution. Lu et al. (2022) calculated the snow depth by applying the methods to the satellite ICESat-2 lidar measurements over the Arctic sea ice, as well as land surfaces of Northern Hemisphere. In this paper, an artificial neural network (ANN) algorithm, employing several channels from Advanced Microwave Scanning Radiometer 2 (AMSR-2) and the humidity vertical profiles from Global Modeling and Assimilation Office (GMAO) Goddard Earth Observing System for Instrument Teams (GEOS-IT) product, is trained to determine snow depth identified by time and geolocation matched 2019 ICESat-2 snow-depth data during winter months over the Arctic sea ice. The trained ANN snow-depth was applied to 2018 AMSR-2 clear pixel data, although the algorithms perform reasonably well in thinner clouds. The validation data (different from the training set) of ANN snow depth from AMSR-2 showed a good agreement with time matched and co-located snow-depth values from ICESat-2. The bias was near zero, with mean absolute error (MAE) 0.05 cm and a root-mean-square-error (RMSE) 0.08 cm. Prior applying the trained ANN snow depth to AMSR-2 data, a cloud screening algorithm was developed with a similar approach. A separate ANN cloud mask was trained to determine an AMSR-2 pixel is clear or cloudy with time and geolocation matched 2015 CALIOP Vertical Feature Mask (VFM) over Arctic sea ice. The ANN cloud mask from AMSR-2 under-estimated cloud fraction by 3-6% compared to CALIOP . The additional research is needed to conclusively evaluate the ANN cloud mask accuracy. Finally, this paper will lay the foundation for a sustained long-term snowfall and snow-storm monitoring system. The future Cloud Aerosol LIdar for Global scale Observations of the ocean-Land Atmosphere system (CALIGOLA) mission will provide a means to calculate snow depth from the lidar backscattering pathlength distribution, benefiting from the UV, visible and infrared pulses. With the calculated snow depth as the truth one could develop a machine learning algorithm, as it was done in this paper, using a passive microwave instrument available at that time to generate a wide range of snow depth data, covering extensive spatial areas in the cross-orbit direction.

Neural Network↗
NASA NTRS1989

Laboratory characterization of direct readout Si:Sb and Si:Ga infrared detector arrays

Highlights of recent results obtained at Ames Research Center in performance evaluations of infrared detector arrays are presented. Antimony- and gallium-doped silicon direct readout 58x62 element hybrid devices from Ames' ongoing detector technology development program are described. The observed characteristics meet most of the performance goals specified by the Space Infrared Telescope Facility (SIRTF) instrument teams and compare favorably with the best performance reported for discrete non-integrating extrinsic silicon detectors. Initial results of radiation environment testing are reported, and non-ideal behavior demonstrated by these test devices is discussed.

Mckelvey, Mark E.↗