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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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NASA NTRS2014

NASA Extreme Environment Mission Operations: Science Operations Development for Human Exploration

The purpose of NASA Extreme Environment Mission Operations (NEEMO) mission 16 in 2012 was to evaluate and compare the performance of a defined series of representative near-Earth asteroid (NEA) extravehicular activity (EVA) tasks under different conditions and combinations of work systems, constraints, and assumptions considered for future human NEA exploration missions. NEEMO 16 followed NASA's 2011 Desert Research and Technology Studies (D-RATS), the primary focus of which was understanding the implications of communication latency, crew size, and work system combinations with respect to scientific data quality, data management, crew workload, and crew/mission control interactions. The 1-g environment precluded meaningful evaluation of NEA EVA translation, worksite stabilization, sampling, or instrument deployment techniques. Thus, NEEMO missions were designed to provide an opportunity to perform a preliminary evaluation of these important factors for each of the conditions being considered. NEEMO 15 also took place in 2011 and provided a first look at many of the factors, but the mission was cut short due to a hurricane threat before all objectives were completed. ARES Directorate (KX) personnel consulted with JSC engineers to ensure that high-fidelity planetary science protocols were incorporated into NEEMO mission architectures. ARES has been collaborating with NEEMO mission planners since NEEMO 9 in 2006, successively building upon previous developments to refine science operations concepts within engineering constraints; it is expected to continue the collaboration as NASA's human exploration mission plans evolve.

Bell, Mary S.↗

NASA NTRS1992

Materials surface contamination analysis

The original research objective was to demonstrate the ability of optical fiber spectrometry to determine contamination levels on solid rocket motor cases in order to identify surface conditions which may result in poor bonds during production. The capability of using the spectral features to identify contaminants with other sensors which might only indicate a potential contamination level provides a real enhancement to current inspection systems such as Optical Stimulated Electron Emission (OSEE). The optical fiber probe can easily fit into the same scanning fixtures as the OSEE. The initial data obtained using the Guided Wave Model 260 spectrophotometer was primarily focused on determining spectra of potential contaminants such as HD2 grease, silicones, etc. However, once we began taking data and applying multivariate analysis techniques, using a program that can handle very large data sets, i.e., Unscrambler 2, it became apparent that the techniques also might provide a nice scientific tool for determining oxidation and chemisorption rates under controlled conditions. As the ultimate power of the technique became recognized, considering that the chemical system which was most frequently studied in this work is water + D6AC steel, we became very interested in trying the spectroscopic techniques to solve a broad range of problems. The complexity of the observed spectra for the D6AC + water system is due to overlaps between the water peaks, the resulting chemisorbed species, and products of reaction which also contain OH stretching bands. Unscrambling these spectral features, without knowledge of the specific species involved, has proven to be a formidable task.

Workman, Gary L.↗

NASA NTRS1991

FLARE: The Far Side Lunar Research Expedition. A design of a far side lunar observatory

This document outlines the design completed by members of Lone Star Aerospace, Inc. (L.S.A.) of a lunar observatory on the far side of the Moon. Such a base would not only establish a long term human presence on the Moon, but would also allow more accurate astronomical data to be obtained. A lunar observatory is more desirable than an Earth based observatory for the following reasons: instrument weight is reduced due to the Moon's weaker gravity; near vacuum conditions exist on the Moon; the Moon has slow rotation to reveal the entire sky; and the lunar surface is stable for long baseline instruments. All the conditions listed above are favorable for astronomical data recording. The technical aspects investigated in the completion of this project included site selection, mission scenario, scientific instruments, communication and power systems, habitation and transportation, cargo spacecraft design, thermal systems, robotic systems, and trajectory analysis. The site selection group focused its efforts on finding a suitable location for the observatory. Hertzsprung, a large equatorial crater on the eastern limb, was chosen as the base site.

Bishop, David W.↗

NASA NTRS2013

Advances in SPICE Support of Planetary Science

SPICE is the de facto international standard for determining the geometric conditions-parameters such as altitude, lighting angles, and LAT/LON coverage of an instrument footprint-pertaining to scientific observations acquired by instruments on board robotic spacecraft. This system, comprised of data and allied software, is used for planning science observations and for analyzing the data returned from those observations. Use of SPICE is not a NASA requirement but is recommended by NASA's Planetary Data System and by the International Planetary Data Alliance. Owing in part to its reliability, stability, portability and user support, the use of SPICE has spread to many national space agencies, including those of the U.S., Europe (ESA), Japan, Russia and India. SPICE has been in use since the Magellan mission to Venus and so has many well-known capabilities. But the NAIF Team responsible for implementing SPICE continues to add new features; this presentation describes a number of these.

computational capability↗

NASA NTRSDate not supplied

NASA Life Sciences Portal (NLSP): Supporting Scientific Transparency and Reproducibility

NASA’s Life Sciences Ports (NLSP) serves the scientific community by providing curated data from space life science experiment. The Human Research Program (HRP) with the help of NLSP is currently transforming their life sciences data archive systems and processes to improve compliance with the FAIR principles [1]. Some of these improvements will at the same time support the twin pillars of Open Science [2]: transparency of methods and reproducibility of results. Scientific transparency is marked by the easily intelligible communication of what has been investigated: what were the procedures for collecting sample and the characteristics of samples collected? what kinds of measurements were made, what were the environmental conditions of the measurements? What were the analysis techniques of the collected data? Reproducibility of the results and findings from the investigation requires a high level of transparency for all but the simplest investigations; the slightest deviation in communicating and replicating complex experimental procedures or data analyses can often yield quite different data and even findings, thwarting their validation. One of the ways the NLSP is aiming to improve the communication of scientific information is through the use of ontology-driven metadata. Ontologies are powerful, graph-based knowledge representation structures, which can be leveraged to increase data interoperability, the area of the FAIR principles in which many data systems most lack compliance. Over the past decade, there has been a concerted effort in the biomedical community to develop modular and narrowly focused domain and application-specific ontologies in a common, open-source framework, the Open Biological and Biomedical Ontology (OBO) Foundry [3]. The open sharing and modular nature of this effort promises huge increases in harmonized data sharing for systems that leverage these models. Which is in line with the FAIR Data Principles of Findability, Accessibility, Interoperability, and Reuse for scientific data management and stewardship. 1. Wilkinson, M.D., et al., The FAIR Guiding Principles for scientific data management and stewardship. Sci Data, 2016. 3: p. 160018. 2. National Academies of Sciences, E. and Medicine, Open Science by Design: Realizing a Vision for 21st Century Research. 2018, Washington, DC: The National Academies Press. 232. 3. Smith, B., et al., The OBO Foundry: coordinated evolution of ontologies to support biomedical data integration. Nat Biotechnol, 2007. 25(11): p. 1251-5.

Life Sciences data↗

NASA NTRSDate not supplied

NASA Life Sciences Portal (NLSP): Supporting Scientific Transparency and Reproducibility

Life Sciences data↗

NASA NTRS1994

Small satellite space operations

CTA Space Systems has played a premier role in the development of the 'lightsat' programs of the 80's and 90's. The high costs and development times associated with conventional LEO satellite design, fabrication, launch, and operations continue to motivate the development of new methodologies, techniques, and generally low cost and less stringently regulated satellites. These spacecraft employ low power 'lightsat' communications (versus TDRSS for NASA's LEO's) and typically fly missions with payload/experiment suites that can succeed, for example, without heavily redundant backup systems and large infrastructures of personnel and ground support systems. Such small yet adaptable satellites are also typified by their very short contract-to-launch times (often one to two years). This paper reflects several of the methodologies and perspectives of our successful involvement in these innovative programs and suggests how they might relieve NASA's mounting pressures to reduce the cost of both the spacecraft and their companion mission operations. It focuses on the use of adaptable, sufficiently powerful yet inexpensive PC-based ground systems for wide ranging user terminal (UT) applications and master control facilities for mission operations. These systems proved themselves in successfully controlling more than two dozen USAF, USN, and ARPA satellites at CTA/SS. UT versions have linked with both GEO and LEO satellites and functioned autonomously in relay roles often in remote parts of the world. LEO applications particularly illustrate the efficacy of these concepts since a user can easily mount a lightweight antenna, usually an omni or helix with light duty rotors and PC-based drivers. A few feet of coax connected to a small transceiver module (the size of a small PC) and a serial line to an associated PC establishes a communications link and together with the PC constitute a viable ground station. Applications included geomagnetic mapping; spaceborne solid state recorder validation; global store-and-forward data communications for both scientific and military purposes such as Desert Storm; UHF transponder services for both digital data and voice using a constellation; remote sensor monitoring of weather and oceanographic conditions; classified payloads; and UHF spectrum surveillance. Ground processing has been accomplished by automatic unattended or manual operation. Management of multiple assets highlights the relative ease with which two constellations totaling nine satellites were controlled from one system including constellation station keeping. Our experience in small end-to-end systems including concurrent design, development, and testing of the flight and operational ground systems offers low cost approaches to NASA scientific satellite operations of the 1990's.

Reiss, Keith↗

NASA NTRS2003

Resource Management for Real-Time Adaptive Agents

Increased autonomy and automation in onboard flight systems offer numerous potential benefits, including cost reduction and greater flexibility. The existence of generic mechanisms for automation is critical for handling unanticipated science events and anomalies where limitations in traditional control software with fixed, predetermined algorithms can mean loss of science data and missed opportunities for observing important terrestrial events. We have developed such a mechanism by adding a Hierarchical Agent-based ReaLTime technology (HART) extension to our Dynamic Resource Management (DRM) middleware. Traditional DRM provides mechanisms to monitor the realtime performance of distributed applications and to move applications among processors to improve real-time performance. In the HART project we have designed and implemented a performance adaptation mechanism to improve reaktime performance. To use this mechanism, applications are developed that can run at various levels of quality. The DRM can choose a setting for the quality level of an application dynamically at run-time in order to manage satellite resource usage more effectively. A groundbased prototype of a satellite system that captures and processes images has also been developed as part of this project to be used as a benchmark for evaluating the resource management framework A significant enhancement of this generic mission-independent framework allows scientists to specify the utility, or "scientific benefit," of science observations under various conditions like cloud cover and compression method. The resource manager then uses these benefit tables to determine in redtime how to set the quality levels for applications to maximize overall system utility as defined by the scientists running the mission. We also show how maintenance functions llke health and safety data can be integrated into the utility framework. Once thls framework has been certified for missions and successfully flight tested it can be reused with little development overhead for other missions. In contrast, current space missions llke Swift manage similar types of resource trade -off completely with the scientific application code itself, and such code must be re-certified and tested for each mission even if a large portion of the code base is shared. This final report discusses some of the major issues motivating this research effort, provides a literature review of the related work, discusses the resource management framework and ground-based satellite system prototype that has been developed, indicates what work is yet to be performed, and provides a list of publications resulting from this work.

Welch, Lonnie↗

DOE OSTI2024

A methodology to develop multi-physics dynamic fuel cell system models validated with vehicle realistic drive cycle data

Fuel cell (FC) technology has been identified as a technically attractive solution to decarbonize the transportation sector, especially for heavy-duty vehicles. In this context, the industry and the scientific community are in need of advanced fuel cell systems (FCS) models that are able to replicate real -world operating conditions. Due to the scarcity of said models in the open literature, this study aimed to develop a comprehensive methodology to calibrate and validate multi -physics dynamic FCS models. Therefore, the key contribution of this paper is the detailed description of the calibration process for each component and the calibration order. The specific focus here was to accurately describe the behavior of the FC stack as well as the cathode, anode, and cooling circuits of the balance of plant. The model was calibrated with the aid of experimental data from a Toyota Mirai FC electric vehicle, which was predominantly retrieved from the vehicle's Controller Area Network (CAN) bus system thereby negating the need for major intrusion into the powertrain system. The validation process was deemed successful with the model being able to truthfully replicate the characteristics of the FC vehicle operated on the World-wide harmonized Light duty Test Cycle (WLTC) 3b and US06 driving cycle. The time -resolved physical parameters such as the cathode pressure, mass flow, or the FC stack temperature were captured with high fidelity, while the overall performance parameters such as the H2 consumption in the stack and the system, and the compressor energy consumption were predicted accurately with a deviation lower than 0.47%, 1.75% and 1.89% with respect to the experimental data, respectively.

Lopez-Juarez, Marcos↗

DOE OSTI2025

Modular Autonomous Experimentation for Biological Applications (Full Report)

The Modular Autonomous Research System (MARS) was developed to address the pressing need for faster, more reliable, and more adaptable scientific discovery. Traditional experimentation is limited by manual labor, long cycle times, and fragmented data streams, which constrain the ability to explore complex chemical and materials design spaces. To overcome these limitations, we created an integrated, modular platform that combines laboratory robotics, diverse measurement instruments, and a central data infrastructure with artificial intelligence–driven decision-making. The system links liquid handling robots, robotic arms, and optical plate readers into a closed loop where experiments are executed automatically, data is analyzed in real time, and subsequent experimental conditions are adaptively chosen to maximize information gain. Over the course of the project, MARS was validated on two primary test cases—spectroscopic metal–ligand binding assays and peptide-directed mineralization—which highlighted the system’s ability to handle uncertainty and variability in experimental measurements. To further demonstrate modularity and extensibility, we also established additional testbeds in electrochemistry for catalyst discovery and electrolyte formulation for advanced batteries. The results show that MARS can reliably conduct autonomous campaigns with minimal human intervention, adapt to distinct scientific domains, and provide a scalable model for future self-driving laboratories. This work establishes new capabilities for modular, uncertainty-aware automation and directly supports the need for advanced, data-driven research platforms capable of accelerating discovery across a wide range of scientific and national security missions.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2019

Managing genomic variant calling workflows with Swift/T

Bioinformatics research is frequently performed using complex workflows with multiple steps, fans, merges, and conditionals. This complexity makes management of the workflow difficult on a computer cluster, especially when running in parallel on large batches of data: hundreds or thousands of samples at a time. Scientific workflow management systems could help with that. Many are now being proposed, but is there yet the “best” workflow management system for bioinformatics? Such a system would need to satisfy numerous, sometimes conflicting requirements: from ease of use, to seamless deployment at peta- and exa-scale, and portability to the cloud. We evaluated Swift/T as a candidate for such role by implementing a primary genomic variant calling workflow in the Swift/T language, focusing on workflow management, performance and scalability issues that arise from production-grade big data genomic analyses. In the process we introduced novel features into the language, which are now part of its open repository. Additionally, we formalized a set of design criteria for quality, robust, maintainable workflows that must function at-scale in a production setting, such as a large genomic sequencing facility or a major hospital system. The use of Swift/T conveys two key advantages. (1) It operates transparently in multiple cluster scheduling environments (PBS Torque, SLURM, Cray aprun environment, etc.), thus a single workflow is trivially portable across numerous clusters. (2) The leaf functions of Swift/T permit developers to easily swap executables in and out of the workflow, which makes it easy to maintain and to request resources optimal for each stage of the pipeline. While Swift/T’s data-level parallelism eliminates the need to code parallel analysis of multiple samples, it does make debugging more difficult, as is common for implicitly parallel code. Nonetheless, the language gives users a powerful and portable way to scale up analyses in many computing architectures.

Science & Technology - Other Topics↗

NASA NTRS2008

The NPOESS Preparatory Project (NPP) Science Data Segment (SDS) Data Depository and Distribution Element (SD3E) System Architecture

The National Polar-orbiting Operational Environmental Satellite System (NPOESS), the U.S. Government's future low-Earth orbiting satellite system, will monitor global weather and environmental conditions. Serving as a risk reduction for NPOESS, the NPOESS Preparatory Project (NPP) will provide remotely sensed atmospheric, land, ocean, ozone, and sounder data that will serve the meteorological and global climate change scientific communities. The National Aeronautics and Space Administration (NASA) NPP Science Data Segment's (SDS) primary role is to independently assess the quality of the NPP science and environmental data records for their ability to support climate research. The SDS is composed of nine elements; an input element that receives data from the operational agencies and acts as a buffer, a calibration analysis element, five elements devoted to measurement based quality assessment, an element used to test algorithmic improvements, and an element that provides overall science direction. Each element requires a set of sensor specific science data products for their evaluation. There are four NPP sensors that will be flown on the NPP observatory. They are the Visible Infrared Imagining Radiometer Suite (VIIRS), the Advanced Technology Microwave Sounder (ATMS), the Cross-Track Infrared Sounder (CrIS), and the Ozone Mapper/Profiler Suite (OMPS). It is estimated that these four sensors combined will make daily data requests for approximately six terabytes of NPP science products from the operational data providers. As a result, issues associated with duplicate data requests, data transfers of large volumes of diverse products, and data transfer failures raised concerns with respect to the network traffic and bandwidth consumption. Therefore, a central data broker system for receiving and buffering data requests and data products for the SDS was developed. The data element for this system is called the SDS Data Depository and Distribution Element (SD3E). It supports science mission data assessment by assuring the timely and validated acquisition and subsequent transfer of the NPP Science Mission data to the SDS Elements and NPP Science Team. The six science elements that interface with the SD3E span across the NASA Goddard Space Flight Center (GSFC), the NASA Jet Propulsion Laboratory (JPL), and the University of Wisconsin. As the primary communication vehicle for the science elements and science team, the SD3E has an interface to the operational data providers: National Environment Satellite, Data, and Information Service (NESDIS) Interface Data Processing System (IDPS) and the National Oceanic Atmospheric Administration's (NOAA) Comprehensive Large Array-data Stewardship system (CLASS) Archive Data System (ADS), that are responsible for product generation and archive and distribution respectively. The SD3E is designed to be a semi-customizable and semi-automated system. This system is designed to provide flexibility and ease of use for the science users in accessing the latest data products by creating a rolling data cache that temporarily stores the products locally before transferring the data to the SDS Measurement based elements for the land, ocean, atmosphere, sounder, and ozone. This paper describes the design and architecture of one of the nine SDS elements, the SD3E, and how this system has provided a mechanism for efficient data exchange, how it has helped in alleviating some of the network traffic and usage, and how it has contributed to reducing operational costs.

Ho, Evelyn L.↗

DOE OSTI2022

MENUS—Materials engineering by neutron scattering

Materials engineering by neutron scattering (MENUS) at the second target station will be a transformational high-flux, versatile, multiscale materials engineering diffraction beamline with unprecedented new capabilities for the study of complex materials and structures. It will support both fundamental and applied materials research in a broad range of fields. MENUS will combine unprecedented long-wavelength neutron flux and unique detector coverage to enable real-time studies of complex structural and functional materials under external stimuli. The incorporated small angle neutron scattering and transmission/imaging capabilities will extend its sensitivity to larger length scales and higher spatial resolution. Multimodal MENUS will provide crystallographic and microstructure data to the materials science and engineering community to understand lattice strain/phase transition/microstructure/texture evolution in three orthogonal directions in complex material systems under combined extreme applied conditions. Finally, the capabilities of MENUS will open new scientific opportunities and meet the research needs for science challenges to enable studies of a range of phenomena and answer the key questions in material design/exploration, advanced material processing, transformative manufacturing, and material operations of national impacts in our daily life.

47 OTHER INSTRUMENTATION↗

DOE OSTI2018

Modeling I/O Performance Variability Using Conditional Variational Auto Encoders

Storage system performance modeling is crucial for efficient use of heterogeneous shared resources on leadership class computers. Variability in application performance, particularly variability arising from concurrent applications sharing I/O resources, is a major hurdle in the development of accurate performance models. We adopt a deep learning approach based on conditional variational auto encoders (CVAE) for I/O performance modeling, and use it to quantify performance variability. We illustrate our approach using the data collected on Edison, a production supercomputing system at the National Energy Research Scientific Computing Center (NERSC). The CVAE approach is investigated by comparing it to a previously proposed sensitivity-based Gaussian process (GP) model. We find that the CVAE model performs slightly better than the GP model in cases where training and testing data come from different applications, since CVAE can inherently leverage the whole data from multiple applications whereas GP partitions the data and builds separate models for each partition. Hence, the CVAE offers an alternative modeling approach that does not need preprocessing; it has enough flexibility to handle data from a wide variety of applications without changing the inference approach.

I/O perfornance variability↗

NASA NTRS1999

Theory and Modeling in Support of Tether

This final report summarizes the work performed by SAIC's Applied Physics Operation on the modeling and support of Tethered Satellite System missions (TSS-1 and TSS-1R). The SAIC team, known to be Theory and Modeling in Support of Tether (TMST) investigation, was one of the original twelve teams selected in July, 1985 for the first TSS mission. The accomplishments described in this report cover the period December 19, 1985 to September 31, 1999 and are the result of a continuous effort aimed at supporting the TSS missions in the following major areas. During the contract period, the SAIC's TMST investigation acted to: Participate in the planning and the execution on both of the TSS missions; Provide scientific understanding on the issues involved in the electrodynamic tether system operation prior to the TSS missions; Predict ionospheric conditions encountered during the re-flight mission (TSS-lR) based on realtime global ionosounde data; Perform post mission analyses to enhance our understanding on the TSS results. Specifically, we have 1) constructed and improved current collection models and enhanced our understanding on the current-voltage data; 2) investigated the effects of neutral gas in the current collection processes; 3) conducted laboratory experiments to study the discharge phenomena during and after tether-break; and 4) perform numerical simulations to understand data collected by plasma instruments SPES onboard the TSS satellite; Design and produce multi-media CD that highlights TSS mission achievements and convey the knowledge of the tether technology to the general public. Along with discussions of this work, a list of publications and presentations derived from the TMST investigation spanning the reporting period is compiled.

Chang, C. L.↗

NASA NTRS1997

Wake Vortex Field Measurement Program at Memphis, Tennessee: Data Guide

Eliminating or reducing current restrictions in the air traffic control system due to wake vortex considerations would yield increased capacity, decreased delays, and cost savings. Current wake vortex separation standards are widely viewed as very conservative under most conditions. However, scientific uncertainty about wake vortex behavior under different atmospheric conditions remains a barrier to development of an adaptive vortex spacing system. The objective of the wake vortex field measurement efforts during December, 1994 and August, 1995 at Memphis, TN were to record wake vortex behavior for varying atmospheric conditions and types of aircraft. This effort is part of a larger effort by the NASA Langley Research Center to develop an Aircraft Vortex Spacing System (AVOSS) as an element of the Terminal Area Productivity (TAP) program. The TAP program is being performed in concert with the FAA Terminal Air Traffic Control Automation (TATCA) program and ATC Automation. Wake vortex behavior was observed using a mobile continuous-wave (CW) coherent laser Doppler radar (lidar) developed at Lincoln Laboratory. This lidar features a number of improvements over previous systems, including the first-ever demonstration of an automatic wake vortex detection and tracking algorithm.

Campbell, S. D.↗

DOE OSTI2023

Physics-Informed Machine Learning for Modeling and Control of Dynamical Systems

Physics-informed machine learning (PIML) is a set of methods and tools that systematically integrate machine learning (ML) algorithms with physical constraints and abstract mathematical models developed in scientific and engineering domains. As opposed to purely data-driven methods, {PIML} models can be trained from additional information obtained by enforcing physical laws such as energy and mass conservation. More broadly, {PIML} models can include abstract properties and conditions such as stability, convexity, or invariance. The basic premise of {PIML} is that the integration of ML and physics can yield more effective, physically consistent, and data-efficient models. This paper aims to provide a tutorial-like overview of the recent advances in {PIML} for dynamical system modeling and control. Specifically, the paper covers an overview of the theory, fundamental concepts and methods, tools, and applications on topics of: 1) physics-informed learning for system identification; 2) physics-informed learning for control; 3) analysis and verification of {PIML} models; and 4) physics-informed digital twins. The paper is concluded with a perspective on open challenges and future research opportunities.

Nghiem, Truong↗

NASA NTRS2008

IceVal DatAssistant: An Interactive, Automated Icing Data Management System

As with any scientific endeavor, the foundation of icing research at the NASA Glenn Research Center (GRC) is the data acquired during experimental testing. In the case of the GRC Icing Branch, an important part of this data consists of ice tracings taken following tests carried out in the GRC Icing Research Tunnel (IRT), as well as the associated operational and environmental conditions during those tests. Over the years, the large number of experimental runs completed has served to emphasize the need for a consistent strategy to manage the resulting data. To address this situation, the Icing Branch has recently elected to implement the IceVal DatAssistant automated data management system. With the release of this system, all publicly available IRT-generated experimental ice shapes with complete and verifiable conditions have now been compiled into one electronically-searchable database; and simulation software results for the equivalent conditions, generated using the latest version of the LEWICE ice shape prediction code, are likewise included and linked to the corresponding experimental runs. In addition to this comprehensive database, the IceVal system also includes a graphically-oriented database access utility, which provides reliable and easy access to all data contained in the database. In this paper, the issues surrounding historical icing data management practices are discussed, as well as the anticipated benefits to be achieved as a result of migrating to the new system. A detailed description of the software system features and database content is also provided; and, finally, known issues and plans for future work are presented.

Levinson, Laurie H.↗