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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 NTRS2021

On-demand Command and Control of ASTERIA with Cloud-based Ground Station Services

ASTERIA (Arcsecond Space Telescope Enabling Research in Astrophysics) was a 6-unit CubeSat technology demonstration mission that deployed from the International Space Station on November 20th, 2017. After successfully completing its 90-day primary mission that demonstrated arcsecond-level line-of-sight pointing and focal plane thermal stability for exoplanet detection, it entered an extended mission performing onboard software demonstrations to mature technology both in space and on the ground. One of the technologies was a completely cloud-based ground system leveraging Amazon Web Services (AWS) Ground Station service. Announced in December 2018 and launched in May 2019, AWS Ground Station is a fully managed ground station service that aims to reduce the overhead associated with developing and maintaining ground system infrastructure throughout the mission lifecycle. AWS Ground Station makes available the suite of features required for any ground system in support of low-Earth orbit (LEO) and medium-Earth Orbit (MEO) satellite operations on-demand and without setting up or maintaining long-term contracts. Charges are incurred on a per-minute basis for antenna usage during scheduled tracks. Support is available for S-band uplink and downlink, along with X-band narrowband and wideband downlink. Missions that use the service may reserve tracks with any licensed AWS Ground Station antennas located across each service region and have direct access to any AWS services in support of mission operations. The cloud-based architecture built around the AWS Ground Station service greatly enhanced ASTERIA mission operations by enabling end-to-end pass automation, on-demand contact scheduling and contingency planning, along with more efficient data downlink through station availability and station-tostation handovers. It incorporated open-source software, particularly NASA's AMMOS Instrument Toolkit (AIT) and Open Mission Control Technologies (OpenMCT), along with the AWS application programming interfaces (API) to the Ground Station, Elastic Compute Cloud (EC2) and Simple Storage Service (S3) services. After showcasing operability in August 2019, the team continued using and improving this novel ground system architecture until the end of mission in December 2019. This paper describes the cloud-based ground system, how it was designed, tested, and evaluated with an inorbit spacecraft, the operational capabilities that it enabled, along with lessons learned and recommendations for future missions.

Fesq, Lorraine↗
NASA NTRSDate not supplied

An Integrated Recursive Framework for Arbitrarily Multiscale and Multi-fidelity Modeling

The NASA Multiscale Analysis Tool (NAMSAT) serves as a state-of-the-art, “plug and play,” massively multiscale modeling (M3) platform for hierarchical materials and structures. The development of NASMAT has focused on modularity, upgradability and maintainability, interoperability, and utility. Application Program Interfaces (APIs) have been developed to facilitate the integration NASMAT into other programs (commercial, research, and user-defined) as well as the integration of other codes into NASMAT. NASMAT is an integrated, recursive platform that seamlessly allows for an arbitrary number of scales, and a variety of modeling fidelity, in a single, non-linear analysis. Thus, the macroscopic response of a material can be directly linked to the behavior of the microstructure(s), including subscale defects, making it a suitable tool for integrated computational materials engineering (ICME) because . Examples using NASMAT for simulation of polycrystalline metals at elevated temperatures will be presented.

Multiscale Modeling↗
NASA NTRSDate not supplied

The SSRI Knowledge Base Tool: Current Tool Functionality Review and Planned Future Enhancements

NASA’s Small Satellite Reliability Initiative (SSRI), in conjunction with NASA’s Small Spacecraft Systems Virtual Institute (S3VI), has developed the SSRI Knowledge Base to improve mission confidence for small spacecraft. The SSRI Knowledge Base provides vetted, high-quality sources of information on elements that are key to successful small spacecraft missions. These resources include SSRI working group generated documents and presentations in addition to existing guides, publications, standards, software tools, websites, and books. The Knowledge Base is fully searchable, offers downloadable content when possible, and otherwise links to or references content directly from within the tool. All 58 of the planned topic pages that comprise the SSRI Knowledge Base have been recently completed and include over 450 unique resources that are now available for review. Over the past several months significant enhancements to the tool’s capabilities have been developed and implemented. These enhancements consist of the completed baseline content; development of an Application Programming Interface (API); improved user interfaces; scalable and searchable Best Practices and Lessons Learned (BPLL) lists with ratings; and custom website analytics. The SSRI Knowledge Base is a comprehensive and searchable online tool that consolidates and organizes resources, best practices, and lessons learned from previous small spacecraft missions sponsored by NASA, other government agencies, and academia. This free, publicly available tool is available to the entire SmallSat community at: NASA SSRI Knowledge Base | Explore. This presentation will discuss the motivation for and development of the SSRI Knowledge Base, demonstrate the existing tool, share how the smallsat community can get involved and outline plans for further enhancement development. The SSRI is a collaborative activity with broad participation from civil, Department of Defense, and both national and international commercial space systems providers and stakeholders. The S3VI is jointly sponsored by NASA’s Space Technology Mission Directorate and Science Mission Directorate.

Small Spacecraft↗
NASA NTRSDate not supplied

Small Satellite Reliability Initiative (SSRI) Knowledge Base Tool: Update and Future Direction

NASA’s Small Satellite Reliability Initiative (SSRI), in conjunction with NASA’s Small Spacecraft Systems Virtual Institute (S3VI), has developed the SSRI Knowledge Base to improve mission confidence for small spacecraft. The SSRI Knowledge Base is a comprehensive and searchable online tool that consolidates and organizes resources, best practices, and lessons learned from previous small satellite missions sponsored by NASA, other government agencies, and academia. This free, publicly available tool is available to the entire SmallSat community at: NASA SSRI Knowledge Base | Explore. The SSRI Knowledge Base provides vetted, high-quality sources of information on elements that are key to successful small satellite missions. These resources include SSRI working group generated documents and presentations in addition to existing guides, publications, standards, software tools, websites, and books. The Knowledge Base is fully searchable, offers downloadable content when possible, and otherwise links to or references content directly from within the tool. All 58 of the planned topic pages that comprise the SSRI Knowledge Base have been recently completed and include over 450 unique resources that are now available for review. Over the past several months significant enhancements to the tool’s capabilities have been developed and implemented. These enhancements consist of the completed baseline content; development of an Application Programming Interface (API); improved user interfaces; scalable and searchable Best Practices and Lessons Learned (BPLL) lists with ratings; and custom website analytics. This presentation and paper will discuss the motivation for and development of the SSRI Knowledge Base, demonstrate the existing tool, and outline plans for further development. The SSRI is a collaborative activity with broad participation from civil, Department of Defense, and both national and international commercial space systems providers and stakeholders. The S3VI is jointly sponsored by NASA’s Space Technology Mission Directorate and Science Mission Directorate.

Small Spacecraft↗
NASA NTRSDate not supplied

Development of Improved Thermal Analysis Capabilities at the NASA Goddard Space Flight Center

Goddard Space Flight Center (GSFC) has been developing a framework of additional analysis capabilities to aid in the verification, development, and execution of thermal models using the OpenTD Application Programming Interface (API). This paper provides a brief overview of the data structures, properties, methods, and relationships between the objects accessible through the current API and describes some of the algorithms necessary to implement the desired functions at GSFC. Some example code snippets are also provided to aid potential users in the development of their own utilities. Following the overview are descriptions and algorithm methodologies of the new capabilities added to the GSFC framework, including: a new PI heater/controller approach for improved steady state predictions, selective copying of symbol over-rides from one source CaseSet to destination CaseSet(s), comparison of submodel object counts between a source and destination model to verify model integration, comparison of thermo-optical and thermo-physical properties between models, and improved display of extracted thermo-optical and thermo-physical properties for documentation.

ThermalDesktop, API, v6.2, OpenTD↗
NASA NTRSDate not supplied

Small Satellite Reliability Initiative (SSRI) Knowledge Base Tool: Use Case Review and Future Functionality and Content Direction

NASA’s Small Satellite Reliability Initiative (SSRI), in conjunction with NASA’s Small Spacecraft Systems Virtual Institute (S3VI), has developed the SSRI Knowledge Base to improve mission confidence for small spacecraft. The SSRI Knowledge Base is a comprehensive and searchable online tool that consolidates and organizes resources, best practices, and lessons learned from previous small satellite missions sponsored by NASA, other government agencies, and academia. This free, publicly available tool is available to the entire SmallSat community at: NASA SSRI Knowledge Base | Explore. The SSRI Knowledge Base provides vetted, high-quality sources of information on elements that are key to successful small satellite missions. These resources include SSRI working group generated documents and presentations in addition to existing guides, publications, standards, software tools, websites, and books. The Knowledge Base is fully searchable, offers downloadable content when possible, and otherwise links to or references content directly from within the tool. All 58 of the planned topic pages that comprise the SSRI Knowledge Base have been recently completed and include over 450 unique resources that are now available for review. Over the past several months significant enhancements to the tool’s capabilities have been developed and implemented. These enhancements consist of the completed baseline content; development of an Application Programming Interface (API); improved user interfaces; scalable and searchable Best Practices and Lessons Learned (BPLL) lists with ratings; and custom website analytics. This presentation and paper will discuss the motivation for and development of the SSRI Knowledge Base, review of potential use case(s), and outline plans for further development and content generation. The SSRI is a collaborative activity with broad participation from civil, Department of Defense, and both national and international commercial space systems providers and stakeholders. The S3VI is jointly sponsored by NASA’s Space Technology Mission Directorate and Science Mission Directorate.

Small Spacecraft↗
NASA NTRS2022

Automating Surface Attitude Positioning and Pointing Operations for Mars 2020

The Surface Attitude Positioning and Pointing (SAPP) subsystem of the Mars Perseverance rover keeps track of the rover’s position and attitude on the surface of Mars. The SAPP Downlink Engineering Operations team members receive data from the rover on a daily basis. They must interpret the data to make sure the rover is staying safe and to support uplink planning. The SAPP team keeps track of the error growth in the rover’s attitude estimate due to noise in the Rover Inertial Measurement Unit’s (RIMU) gyroscopes used to propagate that attitude estimate whenever the rover is moving. Whenever this error grows to a particular threshold, SAPP is responsible for updating the onboard attitude knowledge using the RIMU’s accelerometers to estimate rover roll and pitch and sun imaging to estimate rover yaw, thereby reducing this attitude estimation error. Accurate attitude estimation is required so that the rover can successfully point its High Gain Antenna (HGA) to receive information from Earth and as a backup to the Mars orbiters used for sending data from the rover to Earth, point instruments on its Remote Sensing Mast (RSM), and support safe movement and placement of instruments by the rover’s ARM relative to the Martian surface. The Mars 2020 Engineering Operations team has been working to increase the operational efficiency of the mission and eventually move to a five-hour timeline for daily operations. In pursuit of this goal, the SAPP Engineering Operations team has automated their downlink process by developing a centralized Jupyter notebook to analyze the data received daily from the rover. The SAPP downlink Jupyter notebook automatically collects the data relevant to the SAPP subsystem and visualizes this information in plots and tables that can be easily read by downlink operators to aid them in assessing the status of the subsystem. Various Application Programming Interfaces (APIs) have been incorporated into the downlink daily notebook to automate the collection and posting of data, such as gathering and posting data products to the cloud. The SAPP team has also developed a SAPP downlink software library that includes functions to aid the notebook in processing data. In addition to assessing the SAPP subsystem on a daily basis, operators need to assess the long-term trending behavior of the subsystem over time. An automated trending process has been developed to collect information from the daily notebooks in order to plot and analyze that data in a centralized place. These daily and trending processes have expedited the SAPP downlink assessment and laid the groundwork to completely automate the SAPP downlink process so that SAPP operators are unnecessary unless something unexpected occurs. This paper will provide an overview of the functions that the SAPP subsystem carries out on a daily basis, and will then dive into the automations that have been developed for daily and trending downlink assessment. An assessment of the downlink efficiency will be provided, along with a summary of lessons learned and work to go. Finally, the authors will discuss how these types of automated spacecraft health assessments could be more broadly used within mission operations.

Zarifian, Anais↗
NASA NTRSDate not supplied

Machine Learning Airport Surface Model

Future needs of the National Airspace System require decision support tools to adopt a service-oriented architecture in alignment with the FAA’s vision for an Info-Centric NAS. To achieve this, many existing systems will need to undergo a digital transformation from a monolithic decision support tool to a service-oriented architecture where individual services are exposed through well defined Application Programming Interfaces (APIs). To enable this transformation, NASA has developed the Digital Information Platform as a cloud based foundation for development of aviation services with a special focus towards Artificial Intelligence and Machine Learning (ML) services. This paper describes the work required for the transformation of NASA’s legacy surface management system to a real-time ML based decision support system deployed in the cloud. Details of the Machine Learning Operations (MLOps) infrastructure and best practices are described which enabled the end-toend lifecycle management of ML within an integrated software system. Validation results are provided from an operational field evaluation where performance was benchmarked against the legacy approach.

Jeremy Coupe↗
NASA NTRSDate not supplied

RadLab: A Comprehensive Database and Graphical and Programming Interfaces for Biologically Relevant Space Radiation Data

RadLab, a new component of the NASA Open Science Data Repository (OSDR), is a platform built upon a database of radiation data relevant to space biology. RadLab provides visual and programmatic interfaces for interrogation of its database, as well as a submission process for inclusion of data from investigators. The RadLab application programming interface (API) implements a request syntax enabling users to retrieve data filtered by various combinations of parameters (detector type, location, direction, timespan, etc), which are delivered in machine-readable text formats, ready to be ingested by downstream analysis pipelines; while the graphical user interface (GUI) provides easy means to iteratively modify query parameters and incorporates a number of standard analyses and visualizations (time series plots, geospatial visualizations, detector comparison). Investigators from many countries, including US, Russia, Japan, Canada, the Czech Republic, Germany, Hungary, and Italy, have committed to provide data from their instruments located on the ISS; RadLab will also include data from other spacecraft in LEO (e.g., the Space Shuttle, the Mir space station), BLEO (e. g. BioSentinel, Mars Orbiter, among others), and on other celestial bodies (e. g. Chang’e 4, Curiosity). The first release of RadLab has been made available to the public. Once fully operational, RadLab will provide a comprehensive and ever-growing compendium of space radiation data, facilitating straightforward access to multiple types of readings and enabling space biology researchers to perform intercomparisons of detectors and to determine the radiation environment of research missions, both via programmatic retrieval of these data and via the graphical analysis toolkit; as well as a user-friendly submission portal for ingesting data from space agencies and research institutions. Radiation scientists will be able to use RadLab to gain a deeper understanding of the space radiation environment for future human space exploration. The RadLab Working Group has been formed to foster close collaborations among data contributors and users, to identify data sources, to put in place standards for data normalization, to guide the development of features of the analysis toolkit, to establish the use of RadLab in space radiation biology research, and eventually to provide a forum for discussing relevant research issues that can take advantage of RadLab's capabilities.

radiation↗
NASA NTRSDate not supplied

NASA Power: Global Solar Insolation, Meteorological Parameter Data, and Web Services to Support Sustainable Building Design and Operations

The buildings industry is currently striving to adopt green solutions to make infrastructure more energy-efficient in order to meet the 2050 net-zero climate goals. This planning requires reliable environmental datasets that are crucial in designing, building, and maintaining our world’s-built environment, as well as other energy-related processes and investments. This webinar for the National Institute of Building Sciences provides an overview of NASA’s Prediction Of Worldwide Energy Resources (POWER) Project that informs decision-making and development for sustainable building design and operations by enabling public open discovery, efficient access, and convenient distribution of NASA’s Earth Observations and global atmospheric model datasets. POWER’s datastore is comprised of solar radiation and surface meteorology parameters, spanning nearly 40 years of hourly data, that are easily accessible via several access methods and tools to support three focus areas: 1) renewable energy deployment and management, 2) sustainable infrastructure, and 3) agroclimatology applications. POWER and NASA Earth Science both plan future data parameters, updated tools, and improved observations that could directly support U.S. and international sustainable development goals, climate strategies, and building information modeling. To this end, solar data from several NASA projects and meteorological data from NASA assimilation models have already been reformatted and disseminated to the public via a user-friendly web GIS-enabled based data portal through the POWER Project. POWER data is analysis-ready and accessible through an Application Programming Interface (API), ArcGIS Image Services, and the project’s Data Access Viewer enhanced (DAVe), an interactive online tool. The POWER DAVe also features data consistent with ASHRAE Climate Design Conditions and has developed web image services showing Building Climate Zones and their variability. Through those tools, the data can be downloaded into multiple formats that support the infrastructure community, including CSV and Energy Plus Weather (EPW). POWER’s entire data product catalog is available through Amazon Web Services (AWS) Open Data Registry (ODR) via a free and publicly accessible Simple Storage Service (S3). This webinar provides a full overview of the NASA POWER Project's data and services developed in collaboration with the sustainable infrastructure community. Examples of how the renewable energy and building communities have utilized POWER data products to make decisions and a preview of future data product expansion, including climate projections, and web services will also be provided. Additionally, use case stories from our broad community of users will be presented.

Paul W. Stackhouse↗
NASA NTRS2024

Creating Camera Controls for First-Person Camera in VulkanSceneGraph

The way users interact with a virtual, three-dimensional (3D) scene is heavily influenced by the way the camera used to view the scene is controlled. A first-person camera is a common form of camera control for computer programs. Its role is to create an immersive viewer experience, which allows users to traverse a scene as they might in the real world. Allowing for the implementation of the first-person camera makes for a more holistic, well-rounded way to interact with the visualization program. Accomplishing this involves mathematical calculations that define how the camera should be moved for the computer system. These movements equate to the rotation, translation, and scale of the changes. It should be noted that a computer does not inherently process what movement directions (left, right, up, or down) mean. The mathematical equations used define these principles in a way the computer can process. Further aspects to consider are detecting when the camera has moved and how far. This is most frequently accomplished through user |input through external devices. These devices, for the purpose of this report, include mouse input and keyboard input. Additionally, the in-development program this report is referencing works with the VulkanSceneGraph (VSG) library to create the scene and build the base of the camera controls. Although VSG is a powerful library with many capabilities, additional Application Programming Interfaces (APIs) might be needed during development to produce the desired results, as is the case in this program. Through combining proper mathematical calculations, utilizing additional APIs, and implementing the existing VSG library capabilities, implementing first-person camera controls is possible in a 3D scene.

Kristie O'Brien↗
DOE OSTI2026

Evi-Pro Lite API

This application programing interface provides output from NLR's EVI-Pro model and is used to power the EVI-Pro Lite tool at https://afdc.energy.gov/evi-pro-lite. These endpoints provide daily (24-hour) fleet-level charging load profiles for a variety of customizable scenarios.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS2017

Ground System Architectures Workshop GMSEC SERVICES SUITE (GSS): an Agile Development Story

The GMSEC (Goddard Mission Services Evolution Center) Services Suite (GSS) is a collection of tools and software services along with a robust customizable web-based portal that enables the user to capture, monitor, report, and analyze system-wide GMSEC data. Given our plug-and-play architecture and the needs for rapid system development, we opted to follow the Scrum Agile Methodology for software development. Being one of the first few projects to implement the Agile methodology at NASA GSFC, in this presentation we will present our approaches, tools, successes, and challenges in implementing this methodology. The GMSEC architecture provides a scalable, extensible ground and flight system for existing and future missions. GMSEC comes with a robust Application Programming Interface (GMSEC API) and a core set of Java-based GMSEC components that facilitate the development of a GMSEC-based ground system. Over the past few years, we have seen an upbeat in the number of customers who are moving from a native desktop application environment to a web based environment particularly for data monitoring and analysis. We also see a need to provide separation of the business logic from the GUI display for our Java-based components and also to consolidate all the GUI displays into one interface. This combination of separation and consolidation brings immediate value to a GMSEC-based ground system through increased ease of data access via a uniform interface, built-in security measures, centralized configuration management, and ease of feature extensibility.

Software Development/Agile↗
NASA NTRS2008

JAVA Stereo Display Toolkit

This toolkit provides a common interface for displaying graphical user interface (GUI) components in stereo using either specialized stereo display hardware (e.g., liquid crystal shutter or polarized glasses) or anaglyph display (red/blue glasses) on standard workstation displays. An application using this toolkit will work without modification in either environment, allowing stereo software to reach a wider audience without sacrificing high-quality display on dedicated hardware. The toolkit is written in Java for use with the Swing GUI Toolkit and has cross-platform compatibility. It hooks into the graphics system, allowing any standard Swing component to be displayed in stereo. It uses the OpenGL graphics library to control the stereo hardware and to perform the rendering. It also supports anaglyph and special stereo hardware using the same API (application-program interface), and has the ability to simulate color stereo in anaglyph mode by combining the red band of the left image with the green/blue bands of the right image. This is a low-level toolkit that accomplishes simply the display of components (including the JadeDisplay image display component). It does not include higher-level functions such as disparity adjustment, 3D cursor, or overlays all of which can be built using this toolkit.

Edmonds, Karina↗
DOE OSTI2025

MontePy: a Python library for reading, editing, and writing MCNP input files.

The Monte Carlo N-Particle (MCNP) radiation transport code is a highly capable and accurate code with a long legacy. MCNP uses the Monte Carlo simulation process to simulate the path of particles (e.g., neutrons, photons, charged particles, etc.), and their interaction with materials. It is widely used in nuclear engineering, high-energy physics, and other fields. Its origins in the mid-twentieth century predate many modern software conventions. MCNP users provide an input file to MCNP, which it then uses to create an internal representation of the simulation problem. These input files originally had to be stored as punchcard decks, and the user manual still uses the terminology of cards and decks, despite moving beyond punchcards. MCNP predates nearly all modern human readable markup or data serialization languages, such as the extensible Markup Language (XML), the Standard Generalized Markup Language (SGML), YAML (YAML Ain’t Markup Language), and Javascript Object Notation (JSON). Due to this, MCNP uses an entirely custom defined syntax language for its input, making off-the-shelf libraries for XML, YAML, and JSON impossible to use for scripting various operations on MCNP input files (Kulesza et al., 2022).

97 - MATHEMATICS AND COMPUTING↗
NASA NTRS1994

Integrating UniTree with the data migration API

The Data Migration Application Programming Interface (DMAPI) has the potential to allow developers of open systems Hierarchical Storage Management (HSM) products to virtualize native file systems without the requirement to make changes to the underlying operating system. This paper describes advantages of virtualizing native file systems in hierarchical storage management systems, the DMAPI at a high level, what the goals are for the interface, and the integration of the Convex UniTree+HSM with DMAPI along with some of the benefits derived in the resulting product.

Schrodel, David G.↗
NASA NTRS2013

JPL Space Telecommunications Radio System Operating Environment

A flight-qualified implementation of a Software Defined Radio (SDR) Operating Environment for the JPL-SDR built for the CoNNeCT Project has been developed. It is compliant with the NASA Space Telecommunications Radio System (STRS) Architecture Standard, and provides the software infrastructure for STRS compliant waveform applications. This software provides a standards-compliant abstracted view of the JPL-SDR hardware platform. It uses industry standard POSIX interfaces for most functions, as well as exposing the STRS API (Application Programming In terface) required by the standard. This software includes a standardized interface for IP components instantiated within a Xilinx FPGA (Field Programmable Gate Array). The software provides a standardized abstracted interface to platform resources such as data converters, file system, etc., which can be used by STRS standards conformant waveform applications. It provides a generic SDR operating environment with a much smaller resource footprint than similar products such as SCA (Software Communications Architecture) compliant implementations, or the DoD Joint Tactical Radio Systems (JTRS).

Lux, James P.↗
NASA NTRS1992

PCIPS 2.0: Powerful multiprofile image processing implemented on PCs

Over the years, the processing power of personal computers has steadily increased. Now, 386- and 486-based PC's are fast enough for many image processing applications, and inexpensive enough even for amateur astronomers. PCIPS is an image processing system based on these platforms that was designed to satisfy a broad range of data analysis needs, while requiring minimum hardware and providing maximum expandability. It will run (albeit at a slow pace) even on a 80286 with 640K memory, but will take full advantage of bigger memory and faster CPU's. Because the actual image processing is performed by external modules, the system can be easily upgraded by the user for all sorts of scientific data analysis. PCIPS supports large format lD and 2D images in any numeric type from 8-bit integer to 64-bit floating point. The images can be displayed, overlaid, printed and any part of the data examined via an intuitive graphical user interface that employs buttons, pop-up menus, and a mouse. PCIPS automatically converts images between different types and sizes to satisfy the requirements of various applications. PCIPS features an API that lets users develop custom applications in C or FORTRAN. While doing so, a programmer can concentrate on the actual data processing, because PCIPS assumes responsibility for accessing images and interacting with the user. This also ensures that all applications, even custom ones, have a consistent and user-friendly interface. The API is compatible with factory programming, a metaphor for constructing image processing procedures that will be implemented in future versions of the system. Several application packages were created under PCIPS. The basic package includes elementary arithmetics and statistics, geometric transformations and import/export in various formats (FITS, binary, ASCII, and GIF). The CCD processing package and the spectral analysis package were successfully used to reduce spectra from the Nordic Telescope at La Palma. A photometry package is also available, and other packages are being developed. A multitasking version of PCIPS that utilizes the factory programming concept is currently under development. This version will remain compatible (on the source code level) with existing application packages and custom applications.

Smirnov, O. M.↗