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All sourcesNASA NTRSDOE OSTI
NASA NTRS2019

Bayesian Inference and the Effects of Varying Uncertainty Models in Charring Ablator Calibration and Uncertainty Quantification Problems

The Mars Science Laboratory (MSL) vehicle utilized a heat shield constructed from NASA’s Phenolic-Impregnated Carbon Ablator (PICA) material to protect the main structure from the high enthalpy environment encountered during hypersonic atmospheric entry. During the vehicle’s descent through Martian atmosphere, multiple thermocouples embedded within the heat shield captured in-depth material temperature data that allow for studies to be conducted on current material response reconstruction tools. In the present work, material temperature data obtained from thermocouples within the MISP-4 plug (MEDLI (Mars Science Laboratory Entry, Descent, and Landing Instrument) Integrated Sensor Plug) are utilized in the calibration of Theoretical Ablative Composite for Open Testing (TACOT) model parameters in conjunction with NASA’s Porous material Analysis Toolbox (PATO) through Bayesian inference where uncertainty due to parametric, modeling, and experimental sources is simultaneously quantified. Prior to the study, a sensitivity analysis is performed through computation of the robust Sobol indices in an effort to study the relationship between input space and model response and to reduce the dimensionality of the statistical inverse problem. The Bayesian inference methodology necessitates an a-priori choice to be made for the uncertainty model for which numerous possibilities are available. Across most works, however, only basic additive or multiplicative models are utilized with pre-defined magnitudes of uncertainty based on a-priori knowledge or to-be-calibrated multipliers of static covariance matrix structures. The present effort explores the effects of informed uncertainty models, ones with temporal dependence that are simultaneously calibrated through Bayesian inference, on calibrated results for parameters that make up the uncertain input space.

Sensitivity Analysis↗
NASA NTRS2016

Application of Design of Experiments and Surrogate Modeling within the NASA Advanced Concepts Office, Earth-to-Orbit Design Process

Decisions made during early conceptual design have a large impact upon the expected life-cycle cost (LCC) of a new program. It is widely accepted that up to 80% of such cost is committed during these early design phases. Therefore, to help minimize LCC, decisions made during conceptual design must be based upon as much information as possible. To aid in the decision making for new launch vehicle programs, the Advanced Concepts Office (ACO) at NASA Marshall Space Flight Center (MSFC) provides rapid turnaround pre-phase A and phase A concept definition studies. The ACO team utilizes a proven set of tools to provide customers with a full vehicle mass breakdown to tertiary subsystems, preliminary structural sizing based upon worst-case flight loads, and trajectory optimization to quantify integrated vehicle performance for a given mission. Although the team provides rapid turnaround for single vehicle concepts, the scope of the trade space can be limited due to analyst availability and the manpower requirements for manual execution of the analysis tools. In order to enable exploration of a broader design space, the ACO team has implemented an advanced design methods (ADM) based approach. This approach applies the concepts of design of experiments (DOE) and surrogate modeling to more exhaustively explore the trade space and provide the customer with additional design information to inform decision making. This paper will first discuss the automation of the ACO tool set, which represents a majority of the development effort. In order to fit a surrogate model within tolerable error bounds a number of DOE cases are needed. This number will scale with the number of variable parameters desired and the complexity of the system's response to those variables. For all but the smallest design spaces, the number of cases required cannot be produced within an acceptable timeframe using a manual process. Therefore, automation of the tools was a key enabler for the successful application of an ADM approach to an ACO design study. Following the overview of the tool set automation, an example problem will be given to illustrate the implementation of the ADM approach. The example problem will first cover the inclusion of ground rules and assumptions (GR&A) for a study. The GR&A are very important to the study as they determine the constraints within which a trade study can be conducted. These trades must ultimately reconcile with the customer's desired output and any anticipated "what if" questions. The example problem will then illustrate the setup and execution of a DOE through the automated ACO tools. This process is accomplished more efficiently in this work by splitting the tools into two separate environments. The first environment encompasses the structural optimization and mass estimation tools, while the second is focused on trajectory optimization. Surrogate models are fit to the outputs of each environment and are "integrated" via connection of the surrogate equations. Throughout this process, checks are implemented to compare the output of the surrogates to the output of manually run cases to ensure that the error of the final surrogates is at an acceptable level. The conclusion of the example problem demonstrates the utility of the ADM based approach. Using surrogate models gives the ACO team the ability to visualize vehicle sensitivities to various design parameters and identify regions of interest within the design space. The ADM approach can thus be used to inform concept down selection and isolate promising vehicle configurations to be explored in more detail through the manual design process. In addition it provides the customer with an almost instantaneous turnaround on any ''what if" questions that may arise within the bounds of the surrogate model. This approach ultimately expands the ability of the ACO team to provide its customer with broad and rapid turnaround trade studies for launch vehicle conceptual design. The ability to identify a selection of designs which can meet the customer requirements will help ensure lower LCC of launch vehicle designs originating from ACO.

Zwack, Mathew R.↗
NASA NTRS2016

Application of Design of Experiments and Surrogate Modeling within the NASA Advanced Concepts Office, Earth-to-Orbit Design Process

Decisions made during early conceptual design have a large impact upon the expected life-cycle cost (LCC) of a new program. It is widely accepted that up to 80% of such cost is committed during these early design phases.1 Therefore, to help minimize LCC, decisions made during conceptual design must be based upon as much information as possible. To aid in the decision making for new launch vehicle programs, the Advanced Concepts Office (ACO) at NASA Marshall Space Flight Center (MSFC) provides rapid turnaround pre-phase A and phase A concept definition studies. The ACO team utilizes a proven set of tools to provide customers with a full vehicle mass breakdown to tertiary subsystems, preliminary structural sizing based upon worst-case flight loads, and trajectory optimization to quantify integrated vehicle performance for a given mission.2 Although the team provides rapid turnaround for single vehicle concepts, the scope of the trade space can be limited due to analyst availability and the manpower requirements for manual execution of the analysis tools. In order to enable exploration of a broader design space, the ACO team has implemented an Advanced Design Methods (ADM) based approach. This approach applies the concepts of Design of Experiments (DOE) and surrogate modeling to more exhaustively explore the trade space and provide the customer with additional design information to inform decision making. This paper will first discuss the automation of the ACO tool set, which represents a majority of the development e ort. In order to t a surrogate model within tolerable error bounds a number of DOE cases are needed. This number will scale with the number of variable parameters desired and the complexity of the system's response to those variables. For all but the smallest design spaces, the number of cases required cannot be produced within an acceptable timeframe using a manual process. Therefore, automation of the tools was a key enabler for the successful application of an ADM approach to an ACO design study. Following the overview of the tool set automation, an example problem will be given to illustrate the implementation of the ADM approach. The example problem will first cover the inclusion of Ground Rules and Assumptions (GR&A) for a study. The GR&A are very important to the study as they determine the constraints within which a trade study can be conducted. These trades must ultimately reconcile with the customer's desired output and any anticipated \what if" questions. The example problem will then illustrate the setup and execution of a DOE through the automated ACO tools. This process is accomplished more efficiently in this work by splitting the tools into two separate environments. The first environment encompasses the structural optimization and mass estimation tools, while the second is focused on trajectory optimization. Surrogate models are t to the outputs of each environment and are integrated via connection of the surrogate equations. Throughout this process, checks are implemented to compare the output of the surrogates to the output of manually run cases to ensure that the error of the final surrogates is at an acceptable level. The conclusion of the example problem demonstrates the utility of the ADM based approach. Using surrogate models gives the ACO team the ability to visualize vehicle sensitivities to various design parameters and identify regions of interest within the design space. The ADM approach can thus be used to inform concept down selection and isolate promising vehicle configurations to be explored in more detail through the manual design process. In addition it provides the customer with an almost instantaneous turnaround on any \what if" questions that may arise within the bounds of the surrogate model. This approach ultimately expands the ability of the ACO team to provide its customer with broad and rapid turnaround trade studies for launch vehicle conceptual design. The ability to identify a selection of designs which can meet the customer requirements will have the potential to lower LCC of launch vehicle designs originating from ACO.

Zwack, Mathew R.↗
NASA NTRS2009

Active Learning for Directed Exploration of Complex Systems

Physics-based simulation codes are widely used in science and engineering to model complex systems that would be infeasible to study otherwise. Such codes provide the highest-fidelity representation of system behavior, but are often so slow to run that insight into the system is limited. For example, conducting an exhaustive sweep over a d-dimensional input parameter space with k-steps along each dimension requires k(sup d) simulation trials (translating into k(sup d) CPU-days for one of our current simulations). An alternative is directed exploration in which the next simulation trials are cleverly chosen at each step. Given the results of previous trials, supervised learning techniques (SVM, KDE, GP) are applied to build up simplified predictive models of system behavior. These models are then used within an active learning framework to identify the most valuable trials to run next. Several active learning strategies are examined including a recently-proposed information-theoretic approach. Performance is evaluated on a set of thirteen synthetic oracles, which serve as surrogates for the more expensive simulations and enable the experiments to be replicated by other researchers.

oracles↗
NASA NTRS2024

Exploring Earth's Interface with Space: The Scientific Case for a Satellite Mission to the Lower Thermosphere-Ionosphere Transition Region

The ESA-NASA Lower Thermosphere-Ionosphere Science (ENLoTIS) Working Group was formed in May 2022 to cooperatively explore future lower thermosphere-ionosphere (LTI) satellite mission concepts, targeting very low altitudes (100-200 km) with in situ sampling of relevant geophysical parameters associated with the neutral atmosphere, the ionosphere’s plasma, electromagnetic fields, and energetic particles, which, together with modeling, would enable significant advancements in the understanding of neutral-ion interactions and other related science and space weather topics in this critical region of Geospace. The LTI region has been identified as one of considerable interest to both NASA and ESA. Most recently, the Daedalus mission study was carried out under the remit of ESA’s Earth Observation Programmes (EOP) Directorate competitive Earth Explorer 10 pre-feasibility (Phase 0) activities. Furthermore, many NASA studies have also focused on the LTI region, including both directed missions with dipping spacecraft, such as the initial TIMED dual-satellites and the GEC constellation, as well as numerous highly-rated Explorer proposals targeting the LTI. Although the Daedalus mission was not selected, the ESA Advisory Committee on Earth Observation (ACEO) ranked it highly on scientific grounds and encouraged further study activities to mature the concept, exploring potential international collaboration. Subsequent bilateral discussions with NASA’s Science Mission Directorate (SMD) noted that such a concept was in alignment with the 2020 SMD science plan – Science 2020-2024: A Vision for Scientific Excellence – along with other complimentary activities within the NASA Heliophysics Division. Building on NASA’s and ESA’s long history of very successful collaborations, this mutual interest in LTI science led to the establishment of a new inter-agency and cross-discipline science connection, linking the ESA EOP Climate Action, Sustainability and Science Department and the NASA Heliophysics Division. Initial exploratory discussions led to the formation of the ENLoTIS Working Group, which was directed to explore the science case behind a potential joint LTI mission. Members of the ENLoTIS Working Group are listed below, consisting of 7 scientists from ESA Member and Cooperating States and 7 scientists from the United States. The working group held 3 “in person” meetings over the course of 18 months, interspersed with regular virtual meetings on a more frequent basis. This report constitutes their chief findings and recommendations.

thermosphere↗
NASA NTRS1982

Ecological optimality in water-limited natural soil-vegetation systems. I - Theory and hypothesis

The solution space of an approximate statistical-dynamic model of the average annual water balance is explored with respect to the hydrologic parameters of both soil and vegetation. Within the accuracy of this model it is shown that water-limited natural vegetation systems are in stable equilibrium with their climatic and pedologic environments when the canopy density and species act to minimize average water demand stress. Theory shows a climatic limit to this equilibrium above which it is hypothesized that ecological pressure is toward maximization of biomass productivity. It is further hypothesized that natural soil-vegetation systems will develop gradually and synergistically, through vegetation-induced changes in soil structure, toward a set of hydraulic soil properties for which the minimum stress canopy density of a given species is maximum in a given climate. Using these hypotheses, only the soil effective porosity need be known to determine the optimum soil and vegetation parameters in a given climate.

Eagleson, P. S.↗
NASA NTRS2001

Chemical Engineering in Space

The state of the art in launch systems uses chemical propulsion systems, primarily liquid hydrogen and liquid oxygen, to provide the energy necessary to achieve orbit and escape the bonds of Earth's gravity. In the future there may be other means available; however, currently few of these alternatives can compare to the speed or the ease of use provided by cryogenic chemical propulsion agents. Cryogenics, the science and art of producing cold operating conditions, has become increasingly important to our ability to travel within our solar system. The production and transport of cryogenic fuels as well as the long-term storage of these fluids are necessary for mankind to travel within our solar system. It is with great care and at a significant cost that gaseous compounds such as hydrogen and oxygen are liquified and become dense enough to use for rocket fuel. As our explorations move farther away from Earth, we need to address how to produce the necessary fuels to make a complete round-trip. The cost and the size of any expedition to another celestial body are extreme. If we are constrained by the need to take everything necessary (fuel, life support, etc.) for our survival and return, we greatly increase the risk of being able to go. As with the early explorers on Earth, we will need to harvest much of our energy and our life support from the celestial bodies. The in situ production of these energy sources is paramount to success. Due to the current propulsion system designs, the in-situ processes will require liquefaction and the application of cryogenics. The challenge we face for the near future is to increase our understanding of cryogenic long-term storage and off-world production of cryogenic fluids. We must do this all within the boundaries of very restricted size, weight, and robustness parameters so that we may launch these apparatus from Earth and utilize them elsewhere. Miniaturization, efficiency, and physically robust systems will all play a part in making space exploration possible; however, it is cryogenics that will enable all of this to occur.

Lobmeyer, Dennis A.↗
NASA NTRS2006

System Architecture Modeling for Technology Portfolio Management using ATLAS

Strategic planners and technology portfolio managers have traditionally relied on consensus-based tools, such as Analytical Hierarchy Process (AHP) and Quality Function Deployment (QFD) in planning the funding of technology development. While useful to a certain extent, these tools are limited in the ability to fully quantify the impact of a technology choice on system mass, system reliability, project schedule, and lifecycle cost. The Advanced Technology Lifecycle Analysis System (ATLAS) aims to provide strategic planners a decision support tool for analyzing technology selections within a Space Exploration Architecture (SEA). Using ATLAS, strategic planners can select physics-based system models from a library, configure the systems with technologies and performance parameters, and plan the deployment of a SEA. Key parameters for current and future technologies have been collected from subject-matter experts and other documented sources in the Technology Tool Box (TTB). ATLAS can be used to compare the technical feasibility and economic viability of a set of technology choices for one SEA, and compare it against another set of technology choices or another SEA. System architecture modeling in ATLAS is a multi-step process. First, the modeler defines the system level requirements. Second, the modeler identifies technologies of interest whose impact on an SEA. Third, the system modeling team creates models of architecture elements (e.g. launch vehicles, in-space transfer vehicles, crew vehicles) if they are not already in the model library. Finally, the architecture modeler develops a script for the ATLAS tool to run, and the results for comparison are generated.

Thompson, Robert W.↗
NASA NTRS1998

Genetically Engineered Microelectronic Infrared Filters

A genetic algorithm is used for design of infrared filters and in the understanding of the material structure of a resonant tunneling diode. These two components are examples of microdevices and nanodevices that can be numerically simulated using fundamental mathematical and physical models. Because the number of parameters that can be used in the design of one of these devices is large, and because experimental exploration of the design space is unfeasible, reliable software models integrated with global optimization methods are examined The genetic algorithm and engineering design codes have been implemented on massively parallel computers to exploit their high performance. Design results are presented for the infrared filter showing new and optimized device design. Results for nanodevices are presented in a companion paper at this workshop.

Cwik, Tom↗
NASA NTRS2004

CMC Property Variability and Life Prediction Methods for Turbine Engine Component Application

The ever increasing need for lower density and higher temperature-capable materials for aircraft engines has led to the development of Ceramic Matrix Composites (CMCs). Today's aircraft engines operate with >3000"F gas temperatures at the entrance to the turbine section, but unless heavily cooled, metallic components cannot operate above approx.2000 F. CMCs attempt to push component capability to nearly 2700 F with much less cooling, which can help improve engine efficiency and performance in terms of better fuel efficiency, higher thrust, and reduced emissions. The NASA Glenn Research Center has been researching the benefits of the SiC/SiC CMC for engine applications. A CMC is made up of a matrix material, fibers, and an interphase, which is a protective coating over the fibers. There are several methods or architectures in which the orientation of the fibers can be manipulated to achieve a particular material property objective as well as a particular component geometric shape and size. The required shape manipulation can be a limiting factor in the design and performance of the component if there is a lack of bending capability of the fiber as making the fiber more flexible typically sacrifices strength and other fiber properties. Various analysis codes are available (pcGINA, CEMCAN) that can predict the effective Young's Moduli, thermal conductivities, coefficients of thermal expansion (CTE), and various other properties of a CMC. There are also various analysis codes (NASAlife) that can be used to predict the life of CMCs under expected engine service conditions. The objective of this summer study is to utilize and optimize these codes for examining the tradeoffs between CMC properties and the complex fiber architectures that will be needed for several different component designs. For example, for the pcGINA code, there are six variations of architecture available. Depending on which architecture is analyzed, the user is able to specify the fiber tow size, tow spacing, weave parameter, and angle of orientation of fibers. By holding the volume fraction of the fibers constant, variations in tow spacing can be explored for different architectures. The CMC material properties are usually calculated assuming the component is manufactured perfectly. However, this is typically not the case so that a quantification of the material property variability is needed to account for processing and/or manufacturing imperfections. The overall inputs and outputs are presented using a regression software to rapidly investigate the tradeoffs associated with fiber architecture, material properties, and ultimately cost. This information is then propagated through lifing models and Larson-Miller data to assess timehemperature-dependent CMC strength. In addition, a first order cost estimation will be quantified from a current qualitative perspective. This cost estimation includes the manufacturing challenges, such as tooling, as well as the component cost for a particular application. Ultimately, a cost to performance ratio should be established that compares the effectiveness of CMCs to their current rival, nickel superalloys.

Cheplak, Matthew L.↗
NASA NTRS2013

On the Performance Potential of Bioelectrochemical Life Support Systems

An area of growing multi-disciplinary research and revolutionary development for bio-processing on Earth is bioelectrochemical systems. These systems exploit the capability of many microorganisms to act as biocatalysts, enhancing the performance of electrochemical processes which convert low-value materials into valuable products. Many varieties of such processes hold potential value for space exploration as means to recycle metabolic waste and other undesirable materials or insitu resources into oxygen, water, and other valuable substances. However, the wide range of possible reactants, products, configurations, and operating parameters, along with the early stage of development and application on the ground necessitate thorough consideration of which, if any, possibilities could outperform existing technologies and should thus receive investment for space applications. In turn, the decision depends on the theoretical and practical limits of performance and the value of the reactant-product conversions within spaceflight scenarios, and should, to the greatest extent possible, be examined from the perspective of a fully designed, integrated system, rather than as an isolated unit lacking critical components like valves and pumps. Herein, we select a series of possible reactant-product conversions, develop concept process flow diagrams for each, and estimate theoretical and (where sufficient literature data allows) practical performance limitations of each. The objective was to estimate the costs, benefits, and risks of each concept in order to aid strategic decisions in the early-phase technology development effort.

Mansell, J. Matthew↗
NASA NTRS1986

Space station impact experiments

Four processes serve to illustrate potential areas of study and their implications for general problems in planetary science. First, accretional processes reflect the success of collisional aggregation over collisional destruction during the early history of the solar system. Second, both catastrophic and less severe effects of impacts on planetary bodies survivng from the time of the early solar system may be expressed by asteroid/planetary spin rates, spin orientations, asteroid size distributions, and perhaps the origin of the Moon. Third, the surfaces of planetary bodies directly record the effects of impacts in the form of craters; these records have wide-ranging implications. Fourth, regoliths evolution of asteroidal surfaces is a consequence of cumulative impacts, but the absence of a significant gravity term may profoundly affect the retention of shocked fractions and agglutinate build-up, thereby biasing the correct interpretations of spectral reflectance data. An impact facility on the Space Station would provide the controlled conditions necessary to explore such processes either through direct simulation of conditions or indirect simulation of certain parameters.

Schultz, P.↗
NASA NTRS1991

Solar neutrinos and the MSW effect for three-neutrino mixing

Researchers considered three-neutrino Mikheyev-Smirnov-Wolfenstein (MSW) mixing, assuming m sub 3 is much greater than m sub 2 is greater than m sub 1 as expected from theoretical consideration if neutrinos have mass. They calculated the corresponding mixing parameter space allowed by the Cl-37 and Kamiokande 2 experiments. They also calculated the expected depletion for the Ga-71 experiment. They explored a range of theoretical uncertainty due to possible astrophysical effects by varying the B-8 neutrino flux and redoing the MSW mixing calculation.

Shi, X.↗
NASA NTRS1996

(abstract) MCD3 - A Constraint Length 15 Viterbi Decoder

JPL is responsible for many space missions, as part of NASA's continuing unmanned exploration of the solar system. Signals from spacecraft at planetary distances arrive at Earth with poor S/N ratio. To reduce errors, the signals are encoded with an inner code of Viterbi encoding. One of the key parameters of Viterbi encoding is the constraint length. Previous space missions have used a constraint length of 7. Newer missions use 15, to give a considerably improved error correction ability. However, the complexity of the Viterbi decoder is increased so as to be 256 times more complex.

communications↗
NASA NTRS2009

General Purpose Data-Driven Monitoring for Space Operations

As modern space propulsion and exploration systems improve in capability and efficiency, their designs are becoming increasingly sophisticated and complex. Determining the health state of these systems, using traditional parameter limit checking, model-based, or rule-based methods, is becoming more difficult as the number of sensors and component interactions grow. Data-driven monitoring techniques have been developed to address these issues by analyzing system operations data to automatically characterize normal system behavior. System health can be monitored by comparing real-time operating data with these nominal characterizations, providing detection of anomalous data signatures indicative of system faults or failures. The Inductive Monitoring System (IMS) is a data-driven system health monitoring software tool that has been successfully applied to several aerospace applications. IMS uses a data mining technique called clustering to analyze archived system data and characterize normal interactions between parameters. The scope of IMS based data-driven monitoring applications continues to expand with current development activities. Successful IMS deployment in the International Space Station (ISS) flight control room to monitor ISS attitude control systems has led to applications in other ISS flight control disciplines, such as thermal control. It has also generated interest in data-driven monitoring capability for Constellation, NASA's program to replace the Space Shuttle with new launch vehicles and spacecraft capable of returning astronauts to the moon, and then on to Mars. Several projects are currently underway to evaluate and mature the IMS technology and complementary tools for use in the Constellation program. These include an experiment on board the Air Force TacSat-3 satellite, and ground systems monitoring for NASA's Ares I-X and Ares I launch vehicles. The TacSat-3 Vehicle System Management (TVSM) project is a software experiment to integrate fault and anomaly detection algorithms and diagnosis tools with executive and adaptive planning functions contained in the flight software on-board the Air Force Research Laboratory TacSat-3 satellite. The TVSM software package will be uploaded after launch to monitor spacecraft subsystems such as power and guidance, navigation, and control (GN&C). It will analyze data in real-time to demonstrate detection of faults and unusual conditions, diagnose problems, and react to threats to spacecraft health and mission goals. The experiment will demonstrate the feasibility and effectiveness of integrated system health management (ISHM) technologies with both ground and on-board experiments.

Iverson, David L.↗
NASA NTRS1974

Techniques for the analysis of geodynamic effects using laser data

A technique is described by which laser measurements may be used in an explicit definition of geodetic parameters at the one-meter level of resolution. Observations made by a tracking station at the Goddard Space Flight Center of the Beacon Explorer C satellite are analyzed with this technique to yield highly precise measures of perturbations in the satellite's inclination, including the effect of earth and ocean tides and variations in the station's latitude due to polar motion. The tracking configuration is described, and the basic technique is outlined (analysis of six-hour observations with a weighted least squares orbit determination method). Techniques for analyzing orbital errors and inclination perturbations are described, and it is shown that quarter-day spans of laser data can be employed to monitor the inclination of the satellite to the order of 0.01 arcseconds precision over a period of 17 months.

Dunn, P. J.↗
NASA NTRS1981

The nonlinear wave equation for higher harmonics in free-electron lasers

The nonlinear wave equation and self-consistent pendulum equation are generalized to describe free-electron laser operation in higher harmonics; this can significantly extend their tunable range to shorter wavelengths. The dynamics of the laser field's amplitude and phase are explored for a wide range of parameters using families of normalized gain curves applicable to both the fundamental and harmonics. The electron phase-space displays the fundamental physics driving the wave, and this picture is used to distinguish between the effects of high gain and Coulomb forces.

Colson, W. B.↗
NASA NTRS1992

ROSAT data analysis with EXSAS

For the x-ray observatory ROSAT, data from survey and pointed mission phases taken with different focal plane instruments and according to a complex mission timeline have to be handled. Data analysis therefore puts high demands on appropriate software tools. With EXSAS - the Extended Scientific Analysis System developed with an effort of 20 man years by the German ROSAT Scientific Data Center - a comfortable system for the reduction of data from the ROSAT x-ray and XUV instruments has been made available. EXSAS comprises a large collection of application modules as typically required in analyzing data of this wavelength regime and runs as a specific context in the wide-spread ESO-MIDAS environment. EXSAS, completely written in FORTRAN 77, takes full advantage of all the standards used in MIDAS and therefore, reflects the same portability (different UNIX installations and VMS). If required, the FORTRAN code also enables users to adapt the software in an easy way to their specific needs. To maintain independence from the specifics of different operating systems also on the data input side, all ROSAT data redistributed in the widely accepted FITS format. Although EXSAS has been developed specifically for data analysis of the ROSAT instruments, its structural design is sufficiently general to serve equally well also data from other X-ray and XUV instruments. EXSAS analysis modules are grouped into 4 application packages dealing with Data Preparation and Instrument Correction, Spatial Analysis, Spectral Analysis and Timing Analysis. A special EXSAS header, read and updated by each application, maintains the general information transfer on the origin, the history and the parameter space of the data stored in tables and images. About 100 genuine commands (most of which offer several additional options) allow to interactively explore the functionality of the system. Up to now 40 institutes all over the world have requested the EXSAS software. Maintenance and regular updates of the software and the comprehensive documentation are provided by the ROSAT Scientific Data Center at Garching.

Zimmermann, H. U.↗