Search NASA⌕ Search

SEARCH · Search NASA

Results for “General Mission Analysis Tool”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
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.↗
NASA NTRS2015

Rule-Based Flight Software Cost Estimation

This paper discusses the fundamental process for the computation of Flight Software (FSW) cost estimates. This process has been incorporated in a rule-based expert system [1] that can be used for Independent Cost Estimates (ICEs), Proposals, and for the validation of Cost Analysis Data Requirements (CADRe) submissions. A high-level directed graph (referred to here as a decision graph) illustrates the steps taken in the production of these estimated costs and serves as a basis of design for the expert system described in this paper. Detailed discussions are subsequently given elaborating upon the methodology, tools, charts, and caveats related to the various nodes of the graph. We present general principles for the estimation of FSW using SEER-SEM as an illustration of these principles when appropriate. Since Source Lines of Code (SLOC) is a major cost driver, a discussion of various SLOC data sources for the preparation of the estimates is given together with an explanation of how contractor SLOC estimates compare with the SLOC estimates used by JPL. Obtaining consistency in code counting will be presented as well as factors used in reconciling SLOC estimates from different code counters. When sufficient data is obtained, a mapping into the JPL Work Breakdown Structure (WBS) from the SEER-SEM output is illustrated. For across the board FSW estimates, as was done for the NASA Discovery Mission proposal estimates performed at JPL, a comparative high-level summary sheet for all missions with the SLOC, data description, brief mission description and the most relevant SEER-SEM parameter values is given to illustrate an encapsulation of the used and calculated data involved in the estimates. The rule-based expert system described provides the user with inputs useful or sufficient to run generic cost estimation programs. This system's incarnation is achieved via the C Language Integrated Production System (CLIPS) and will be addressed at the end of this paper.

computational intelligence↗
NASA NTRS1997

Mineralogy of the Martian Surface: Crustal Composition to Surface Processes

The main results have been published in the refereed literature, and thus this report serves mainly to summarize the main findings and indicate where the detailed papers may be found. Reflectance spectroscopy has been an important tool for determining the mineralogic makeup of the near surface materials on Mars. Analysis of the spectral properties of the surface have demonstrated that these attributes are heterogeneous from the coarse spatial but high spectral resolution spectra obtained with telescopes to the high spatial but coarse spectral resolution Viking data (e.g. Arvidson et al., 1989; McEwen et al., 1989). Low albedo materials show strong evidence for the presence of igneous rock forming minerals while bright materials are generally interpreted as representing heavily altered crustal material. How these materials are physically and genetically related has important implications for understanding martian surface properties and processes, weathering histories and paths, and crustal composition. The goal of this research is to characterize the physical and chemical properties of low albedo materials on Mars and the relationship to intermediate and high albedo materials. Fundamental science questions to be pursued include: (1) the observed distributions of soil, rock, and dust a function of physical processes or weathering and (2) different stages of chemical and physical alteration fresh rock identified. These objectives will be addressed through detailed analyses and modelling of the ISM data from the Phobos-2 mission with corroborating evidence of surface composition and properties provided by data from the Viking mission.

Mustard, John F.↗
NASA NTRS2011

Software Certification - Coding, Code, and Coders

We describe a certification approach for software development that has been adopted at our organization. JPL develops robotic spacecraft for the exploration of the solar system. The flight software that controls these spacecraft is considered to be mission critical. We argue that the goal of a software certification process cannot be the development of "perfect" software, i.e., software that can be formally proven to be correct under all imaginable and unimaginable circumstances. More realistically, the goal is to guarantee a software development process that is conducted by knowledgeable engineers, who follow generally accepted procedures to control known risks, while meeting agreed upon standards of workmanship. We target three specific issues that must be addressed in such a certification procedure: the coding process, the code that is developed, and the skills of the coders. The coding process is driven by standards (e.g., a coding standard) and tools. The code is mechanically checked against the standard with the help of state-of-the-art static source code analyzers. The coders, finally, are certified in on-site training courses that include formal exams.

training↗
NASA NTRS2001

Challenges Facing Design and Analysis Tools

The design and analysis of future aerospace systems will strongly rely on advanced engineering analysis tools used in combination with risk mitigation procedures. The implications of such a trend place increased demands on these tools to assess off-nominal conditions, residual strength, damage propagation, and extreme loading conditions in order to understand and quantify these effects as they affect mission success. Advances in computer hardware such as CPU processing speed, memory, secondary storage, and visualization provide significant resources for the engineer to exploit in engineering design. The challenges facing design and analysis tools fall into three primary areas. The first area involves mechanics needs such as constitutive modeling, contact and penetration simulation, crack growth prediction, damage initiation and progression prediction, transient dynamics and deployment simulations, and solution algorithms. The second area involves computational needs such as fast, robust solvers, adaptivity for model and solution strategies, control processes for concurrent, distributed computing for uncertainty assessments, and immersive technology. Traditional finite element codes still require fast direct solvers which when coupled to current CPU power enables new insight as a result of high-fidelity modeling. The third area involves decision making by the analyst. This area involves the integration and interrogation of vast amounts of information - some global in character while local details are critical and often drive the design. The proposed presentation will describe and illustrate these areas using composite structures, energy-absorbing structures, and inflatable space structures. While certain engineering approximations within the finite element model may be adequate for global response prediction, they generally are inadequate in a design setting or when local response prediction is critical. Pitfalls to be avoided and trends for emerging analysis tools will be described.

Knight, Norman F., Jr.↗
NASA NTRS2016

Evidence Report: Risk of Performance Errors Due to Training Deficiencies

Substantial evidence supports the claim that inadequate training leads to performance errors. Barshi and Loukopoulos (2012) demonstrate that even a task as carefully developed and refined over many years as operating an aircraft can be significantly improved by a systematic analysis, followed by improved procedures and improved training (see also Loukopoulos, Dismukes, & Barshi, 2009a). Unfortunately, such a systematic analysis of training needs rarely occurs during the preliminary design phase, when modifications are most feasible. Training is often seen as a way to compensate for deficiencies in task and system design, which in turn increases the training load. As a result, task performance often suffers, and with it, the operators suffer and so does the mission. On the other hand, effective training can indeed compensate for such design deficiencies, and can even go beyond to compensate for failures of our imagination to anticipate all that might be needed when we send our crew members to go where no one else has gone before. Much of the research literature on training is motivated by current training practices aimed at current training needs. Although there is some experience with operations in extreme environments on Earth, there is no experience with long-duration space missions where crews must practice semi-autonomous operations, where ground support must accommodate significant communication delays, and where so little is known about the environment. Thus, we must develop robust methodologies and tools to prepare our crews for the unknown. The research necessary to support such an endeavor does not currently exist, but existing research does reveal general challenges that are relevant to long-duration, high-autonomy missions. The evidence presented here describes issues related to the risk of performance errors due to training deficiencies. Contributing factors regarding training deficiencies may pertain to organizational process and training programs for spaceflight, such as when training programs are inadequate or unavailable. Furthermore, failure to match between tasks on the one hand, and learning and memory abilities on the other hand is a contributing factor, especially when individuals' relative efficiency with which new information is acquired, and adjustments made in behavior or thinking, are inconsistent with mission demands. Thus, if training deficiencies are present, the likelihood of errors or of the inability to successfully complete a task increases. What's more, the overall risk to the crew, the vehicle, and the mission increases.

Barshi, Immanuel↗
NASA NTRS2016

Advances in Rodent Research Missions on the International Space Station

A research platform for rodent experiment on the ISS is a valuable tool for advancing biomedical research in space. Capabilities offered by the Rodent Research project developed at NASA Ames Research Center can support experiments of much longer duration on the ISS than previous experiments performed on the Space Shuttle. NASAs Rodent Research (RR)-1 mission was completed successfully and achieved a number of objectives, including validation of flight hardware, on-orbit operations, and science capabilities as well as support of a CASIS-sponsored experiment (Novartis) on muscle atrophy. Twenty C57BL6J adult female mice were launched on the Space-X (SpX) 4 Dragon vehicle, and thrived for up to 37 days in microgravity. Daily health checks of the mice were performed during the mission via downlinked video; all flight animals were healthy and displayed normal behavior, and higher levels of physical activity compared to ground controls. Behavioral analysis demonstrated that Flight and Ground Control mice exhibited the same range of behaviors, including eating, drinking, exploratory behavior, self- and allo-grooming, and social interactions indicative of healthy animals. The animals were euthanized on-orbit and select tissues were collected from some of the mice on orbit to assess the long-term sample storage capabilities of the ISS. In general, the data obtained from the flight mice were comparable to those from the three groups of control mice (baseline, vivarium and ground controls, which were housed in flight hardware), showing that the ISS has adequate capability to support long-duration rodent experiments. The team recovered 35 tissues from 40 RR-1 frozen carcasses, yielding 3300 aliquots of tissues to distribute to the scientific community in the U.S., including NASAs GeneLab project and scientists via Space Biology's Biospecimen Sharing Program Ames Life Science Data Archive. Tissues also were distributed to Russian research colleagues at the Institute for Biomedical Problems. The expression levels of select genes including albumin, catalase, GAPDH, HMGCoA Reductase, and IGF1 were determined using RNA isolated from the livers by qPCR and no significant differences by one factor ANOVA were found between flight and ground control groups. In addition, some of the liver samples were analyzed for transcriptomic, epigenomic and proteomic profiles; some of the data sets are now available to the scientific community through GeneLabs open science data website. A second long duration mission, Rodent Research-2 (RR-2) was completed on the ISS in 2015; 20 female C57BL6J mice were successfully maintained on the ISS for various durations, with the last group of 5 animals living on-orbit for 54 days. Furthermore, we continue to expand the ISSs capabilities by introducing new on-orbit technologies including blood collection and separation, bone densitometry scanning, muscle grip strength and anesthesia with recovery. In addition, series of ground-based verification testing to fly male mice and increase the total number of mice on-orbit from 20 to 40. Subsequent missions will provide the capability to return live mice from the ISS animals to evaluate recovery on Earth, further expanding operational and science capabilities of the RR project on the ISS.

Choi, S. Y.↗
NASA NTRS2009

Modeling and Simulation of Variable Mass, Flexible Structures

The advent of the new Ares I launch vehicle has highlighted the need for advanced dynamic analysis tools for variable mass, flexible structures. This system is composed of interconnected flexible stages or components undergoing rapid mass depletion through the consumption of solid or liquid propellant. In addition to large rigid body configuration changes, the system simultaneously experiences elastic deformations. In most applications, the elastic deformations are compatible with linear strain-displacement relationships and are typically modeled using the assumed modes technique. The deformation of the system is approximated through the linear combination of the products of spatial shape functions and generalized time coordinates. Spatial shape functions are traditionally composed of normal mode shapes of the system or even constraint modes and static deformations derived from finite element models of the system. Equations of motion for systems undergoing coupled large rigid body motion and elastic deformation have previously been derived through a number of techniques [1]. However, in these derivations, the mode shapes or spatial shape functions of the system components were considered constant. But with the Ares I vehicle, the structural characteristics of the system are changing with the mass of the system. Previous approaches to solving this problem involve periodic updates to the spatial shape functions or interpolation between shape functions based on system mass or elapsed mission time. These solutions often introduce misleading or even unstable numerical transients into the system. Plus, interpolation on a shape function is not intuitive. This paper presents an approach in which the shape functions are held constant and operate on the changing mass and stiffness matrices of the vehicle components. Each vehicle stage or component finite element model is broken into dry structure and propellant models. A library of propellant models is used to describe the distribution of mass in the fuel tank or Solid Rocket Booster (SRB) case for various propellant levels. Based on the mass consumed by the liquid engine or SRB, the appropriate propellant model is coupled with the dry structure model for the stage. Then using vehicle configuration data, the integrated vehicle model is assembled and operated on by the constant system shape functions. The system mode shapes and frequencies can then be computed from the resulting generalized mass and stiffness matrices for that mass configuration. The rigid body mass properties of the vehicle are derived from the integrated vehicle model. The coupling terms between the vehicle rigid body motion and elastic deformation are also updated from the constant system shape functions and the integrated vehicle model. This approach was first used to analyze variable mass spinning beams and then prototyped into a generic dynamics simulation engine. The resulting code was tested against Crew Launch Vehicle (CLV-)class problems worked in the TREETOPS simulation package and by Wilson [2]. The Ares I System Integration Laboratory (SIL) is currently being developed at the Marshall Space Flight Center (MSFC) to test vehicle avionics hardware and software in a hardware-in-the-loop (HWIL) environment and certify that the integrated system is prepared for flight. The Ares I SIL utilizes the Ares Real-Time Environment for Modeling, Integration, and Simulation (ARTEMIS) tool to simulate the launch vehicle and stimulate avionics hardware. Due to the presence of vehicle control system filters and the thrust oscillation suppression system, which are tuned to the structural characteristics of the vehicle, ARTEMIS must incorporate accurate structural models of the Ares I launch vehicle. The ARTEMIS core dynamics simulation models the highly coupled nature of the vehicle flexible body dynamics, propellant slosh, and vehicle nozzle inertia effects combined with mass and flexible body properties that vary significant with time during the flight. All forces that act on the vehicle during flight must be simulated, including deflected engine thrust force, spatially distributed aerodynamic forces, gravity, and reaction control jet thrust forces. These forces are used to excite an integrated flexible vehicle, slosh, and nozzle dynamics model for the vehicle stack that simulates large rigid body translations and rotations along with small elastic deformations. Highly effective matrix math operations on a distributed, threaded high-performance simulation node allow ARTEMIS to retain up to 30 modes of flex for real-time simulation. Stage elements that separate from the stack during flight are propagated as independent rigid six degrees of freedom (6DOF) bodies. This paper will present the formulation of the resulting equations of motion, solutions to example problems, and describe the resulting dynamics simulation engine within ARTEMIS.

Tobbe, Patrick A.↗
NASA NTRS1997

Operation of the Planetary Plasma Interactions Node of the Planetary Data System

Five years ago NASA selected the Planetary Plasma Interactions (PPI) Node at UCLA to help the scientific community locate, access and preserve particles and fields data from planetary missions. We propose to continue to serve for 5 more years. During the first five years we have served the scientific community by providing them with high quality data products. We worked with missions and individual scientists to secure the highest quality data possible and to thoroughly document it. We validated the data, placed it on long lasting media and made sure it was properly archived for future use. So far we have prepared and archived over 10(exp 11) bytes of data from 26 instruments on 4 spacecraft. We have produced 106 CD-ROMs with peer reviewed data. In so doing, we have developed an efficient system to prepare and archive the data and thereby have been able to steadily increase the rate at which the data are produced. Although we produced a substantial archive during the initial five years, we have an even larger amount of work in progress. This includes preparing CD-ROM data sets with all of the Voyager, Pioneer and Ulysses data at Jupiter and Saturn. We will have the Jupiter data ready for the Galileo encounter in December, 1995. We are also completing the Pioneer Venus data restoration. The Galileo Venus archive and radio science data from Magellan will be prepared early in the next period. We are assisting the Small Bodies Node of PDS in the preparation of comet data and will be archiving the asteroid data from Galileo. We will be moving in several new directions as well. We will archive the PPI Node's first Earth based data with data from the International Jupiter Watch and Hubble data taken in support of Ulysses particles and field observations. We will work with the Cassini mission in archive planning efforts. For the inner planets we will begin an archive of Mars data starting with Phobos data and will support the US and Russian Mars missions in the late 1990's. We will restore the Mercury data from Mariner 10 and prepare the lunar data from Clementine in time for the lunar data analysis program in 1995. We will work with the Discovery mission teams to plan their archive and have already started with one, NEAR. Finally we will begin archiving our first heliospheric data from Voyager, Galileo, and Mars observers. We will continue to serve the science community by providing access to the data products. During the past 19 months we have filled nearly 6000 requests for on-line and CD-ROM data. The data delivered directly by the PPI Node has been - 5 x 10(exp 11) bytes. In addition to providing the data, we have provided users with software tools to manage and read the data which are computer, operating system and format independent. We have developed scalable systems so that the same software we use to manage and access the data for the entire PPI Node can be used by individual investigators to manage the data on a single CD-ROM, thereby greatly reducing the software development effort for both the PPI Node and users. We deliver this software with the disks. Recent technical advances have made it possible for us to serve a broader community than before. In the next five year period we plan to extend our outreach to the general public and in particular to increase our support for education. Since planetary plasma data are varied and require expertise in many areas the PPI Node will continue to be distributed. In addition to the primary node at UCLA, the PPI Node has three subnodes with an Outer Planets Subnode at the University of Iowa, an Inner Planets Subnode at UCLA, and a Radio Science Subnode at Stanford University. During the first two years of the renewal period there will be a Radio Astronomy Data Node at GSFC. These organizations will provide scientific expertise on the data, participate in node data selection activities and help with data restoration and mission activities.

Walker, Raymond J.↗
NASA NTRSDate not supplied

High-Order Methods in NASA’s Next Generation of Computational Fluid Dynamics Tools

The missions of the National Aeronautics and Space Administration (NASA) routinely produce unique requirements and challenges for development and application of Computational Fluid Dynamics (CFD) methods. NASA presently embodies four distinct Mission Directorates: Aeronautics Research, Exploration Systems, Science, and Space Operations. These missions generate requirements for systems that operate in a wide variety of environments. They range from the high-speed flight of aerodynamically optimized vehicles operating in the earth’s atmosphere to spacecraft designed for missions that don’t favor aerodynamic optimization, some operating in the atmosphere of planets and planetary moons such as Mars and Venus or Saturn’s moon Titan. Systems supporting these vehicles, such as rocket and jet propulsion, reaction control systems, fluid and thermal transfer systems, etc. can also generate their own unique set of flow phenomena that challenge today’s CFD methodology. Through the NASA Engineering and Safety Center (NESC), NASA annually conducts state-of-the-discipline assessments in fifteen distinct engineering disciplines. These assessments are performed by the NASA Technical Fellows that lead Technical Discipline Teams (TDT) of recognized experts in these fifteen areas. In the Aerosciences discipline, three topics have been identified as the top challenges for the discipline: aero-plume interaction prediction, unsteady separated flows, and aerothermodynamic prediction. These challenge areas are defined by the Agency’s high-risk projects and problems on which the NESC is requested to perform independent testing, analysis, and assessments. When viewed as a whole, these tests, analyses, and assessments provide a clear view of the recurring technical challenges facing Agency engineers and researchers and can be used to guide future research and technology development. The present state-of-the-art in the application of CFD at NASA is the use of Reynolds-Averaged Navier- Stokes (RANS) solvers, primarily executed in a steady-state mode of operation. In isolated cases, Unsteady RANS (URANS) solvers have been employed when steady RANS solutions produce poorly converging or oscillating results or in cases, such as aeroelastic analysis, which require unsteady aerodynamic simulation. For most traditional external and internal aerodynamic flows, structured overset grids or unstructured grids are employed to minimize geometric modeling and grid generation times. Grid adaptation, primarily as a series of coarse-grain intermediate processing steps is also seeing use on particularly complex flow problems and configurations. In the case of aerothermodynamic flows, engineers have been forced to continue to employ structured grid techniques as the present unstructured grid methodology has proven inadequate in the prediction of surface heating. In the area of aero-plume interaction modeling, two-gas, frozen chemistry simulation is generally the state-of-the- art, with some production solvers capable of predicting flows with only a single gas component. Prediction of flows falling into the afore-mentioned top Aerosciences technical challenges have severely stressed the present state-of-the-art in CFD prediction and for some problems, such as unsteady separated flows and aero-plume interaction cases, engineers have begun employing Large Eddy Simulation (LES) and Hybrid RANS/LES techniques. In some isolated aero-propulsion interaction cases, chemically reacting flow simulations have been applied. These methods are highly evolutionary and engineers have little experience in their application, so they cannot be heavily relied upon in today’s application environment. Therefore, this leads one to muse over which numerical technologies will be included in the CFD tools that will be employed 30 years in the future. This presentation will describe specific technical problems that have stressed NASA’s traditional CFD methods to their breaking point and will link these issues to the Agency’s top Aerosciences technical challenges. The discussion will then shift to the characteristics of future CFD solvers that will be required to attack these challenges and how these characteristics differ from the present state-of-the- art. High-order methods certainly appear to have a place in the development of future CFD tools and some of the physical characteristics of our most challenging problems suggest that high-order methods are the only way to effectively solve them. But there are some relatively severe implementation issues that face these methods, particularly in the area of general applicability and robust operation as an engineering tool. Desired characteristics of next-generation CFD solvers will be discussed and the author’s view of which emerging numerical technologies might be employed to address these attributes will also be presented

David M Schuster↗
NASA NTRS2016

Managing and Servicing Physical Oceanographic Data at a NASA Distributed Active Archive Center

The NASA Earth Science Data Information Systems Project funds and operates 12 Distributed Active Archive Center(s) (DAAC) throughout the United States. Of these 12 centers, the Physical Oceanography DAAC (PO.DAAC) is committed to providing long term archival, distribution and stewardship for NASA physical oceanographic data, primarily derived from space-born satellite systems, but also including a growing set of recent and future in situ observations from the SPURS-1 and SPURS-2 campaigns. Notable NASA missions supported include: Seasat, TOPEX/Poseidon, NSCAT, QuikSCAT, ISS-RapidScat, Jason-1, Jason-2/OSTM, GRACE, Aquarius, GHRSST, and MODIS. The following interagency and international missions are also supported by PO.DAAC: AVHRR, Coriolis, DMSP, MetOp-A, MetOp-B, Oceansat-2. The PO.DAAC currently holds 525 datasets in public distribution, spanning the following observational parameters: sea surface temperature, sea surface salinity, ocean color, ocean surface currents, ocean surface wind speed, ocean surface wind direction, sea surface height, significant wave height, ocean water mass/thickness, and sea ice age. A hundred of these datasets are available in near-real-time. Datasets are distributed through a variety of open-source access protocols including FTP, OPeNDAP, and THREDDS. FTP will soon be phased out in favor of a recently introduced HTTPS PO.DAAC Drive interface that supports WebDAV and interoperable machine-to-machine communication. OPeNDAP supports remote data/metadata query, subset, and download. THREDDS provides the features of OPeNDAP with the additional feature of temporal aggregation. PO.DAAC also offers proprietary tools and services to further enhance the data discovery, visualization and analysis experience, including but not limited to: State of the Ocean, Web Services (data/metadata discovery and extraction), HiTIDE Level-2 subsetter, Live Access Server (LAS), Webification (w10nsci), and Rich Site Summary (RSS) Datacasting. To assist with provenance of datasets, PO.DAAC has implemented DOIs for the data it distributes so that they can be properly cited. There is a user forum and helpdesk that contains data recipes and via which users can get guidance. In summary, this presentation aims to provide a general overview of PO.DAAC’s web portal and data holdings along with a set of illustrative examples leading prospective data users into the practical utility of its tools and services.

Moroni, David F.↗
NASA NTRS2010

Blunt-Body Entry Vehicle Aerothermodynamics: Transition and Turbulence on the CEV and MSL Configurations

Recent, current, and planned NASA missions that employ blunt-body entry vehicles pose aerothermodynamic problems that challenge the state-of-the art of experimental and computational methods. The issues of boundary-layer transition and turbulent heating on the heat shield have become important in the designs of both the Mars Science Laboratory and Crew Exploration Vehicle. While considerable experience in these general areas exists, that experience is mainly derived from simple geometries; e.g. sharp-cones and flat-plates, or from lifting bodies such as the Space Shuttle Orbiter. For blunt-body vehicles, application of existing data, correlations, and comparisons is questionable because an all, or mostly, subsonic flow field is produced behind the bow shock, as compared to the supersonic (or even hypersonic) flow of other configurations. Because of the need for design and validation data for projects such as MSL and CEV, many new experimental studies have been conducted in the last decade to obtain detailed boundary-layer transition and turbulent heating data on this class of vehicle. In this paper, details of several of the test programs are reviewed. The laminar and turbulent data from these various test are shown to correlate in terms of edge-based Stanton and Reynolds number functions. Correlations are developed from the data for transition onset and turbulent heating augmentation as functions of momentum thickness Reynolds number. These correlation can be employed as engineering-level design and analysis tools.

Hollis, Brian R.↗
NASA NTRS2018

Collaborative Systems Engineering in the Ascent Abort-2 Crew Module/Separation Ring Project

Generally speaking, systems engineering (SE) tool-sets face a dilemma balancing power and accessibility. High-powered SE tools (MagicDraw, Cradle, Core, etc.) tend to be specialized and are available only to highly trained Systems Engineers, and/or through the use of a 'back room' developer team making the output products available to the broader team. On the other hand, highly accessible tools (MS Word, Excel, etc.) do not have the power to implement SE in a rigorous manner. NASA has to test all aspects of the new human-rated Orion Multi-Purpose Crew Vehicle spacecraft prior to its first crewed mission. The test program includes uncrewed launch abort flight tests to demonstrate the capability to save the crew in the event that a launch failure occurs. Orion's second abort flight test will be a low-altitude flight test known as "Ascent Abort 2 (AA-2)." This test is currently scheduled to be carried out at Cape Canaveral Air Force Station's Space Launch Complex 46 (SLC-46) in Florida in 2019. NASA's in-house AA-2 Crew Module and Separation Ring (CSR) Team is producing the crew module and separation ring. Operating jointly as both an Advanced Exploration Systems (AES) Project and an Orion Project, the CSR project charter includes development of innovative, streamlined and generally more efficient practices for creation of flight hardware and software. One result of this tasking has been development of a collaborative and data-centric systems engineering environment within the team's shared web environment (Microsoft SharePoint). Through the use of built-in, 'out of the box capabilities' present in MS SharePoint, the CSR Systems Engineering team has created (with some limited developer support) a data-centric architecture for the project's SE implementation, including functional and interface analysis, requirements development and management, risk management, verification planning and management, test results, and end item management. Data elements are linked between data structures so as to define and control relationships between item types, link requirements to parents and children, and link tests to the requirements that they verify. The overall project team integration is increased by also linking SE content to project management content over the project life cycle, including team communication, action items, configuration management, decisional and meeting materials, and life cycle reviews. This presentation will provide an overview of the collaborative SE environment, showing how it provides the power for a number of SE tasks while still providing the accessibility and transparency to allow the full project team to collaborate and succeed. Given the project phase, we'll be able to present a nearly full lifecycle discussion, from concept through verification and approaching delivery.

Systems Engineering environments↗
NASA NTRS2005

Apex Reference Manual 3.0 Beta

Apex is a toolkit for constructing software that behaves intelligently and responsively in demanding task environments. Reflecting its origin at NASA where Apex continues to be developed, current applications include: a) Providing autonomous mission management and tactical control capabilities for unmanned aerial vehicles including an autonomous surveillance helicopter and a simulation prototype of an unmanned fixed-wing aircraft to be used for wildfire mapping; b) Simulating human air traffic controllers, pilots and astronauts to help predict how people might respond to changes in equipment or procedures; and c) Predicting the precise duration and sequence of routine human behaviors based on a human-computer interaction engineering technique called CPM-GOMS. Among Apex s components are a set of implemented reasoning services, such as those for reactive planning and temporal pattern recognition; a software architecture that embeds and integrates these services and allows additional reasoning elements to be added as extensions; a formal language for specifying agent knowledge; a simulation environment to facilitate prototyping and analysis; and Sherpa, a set of tools for visualizing autonomy logic and runtime behavior. In combination, these are meant to provide a flexible and usable framework for creating, testing, and deploying intelligent agent software. Overall, our goal in developing Apex is to lower economic barriers to developing intelligent software agents. New ideas about how to extend or modify the system are evaluated in terms of their impact in reducing the time, expertise, and inventiveness required to build and maintain applications. For example, potential enhancements to the AI reasoning capabilities in the system are reviewed not only for usefulness and distinctiveness, but also for their impact on the readability and general usability of Apex s behavior representation language (PDL) and on the transparency of resulting behavior. A second central part of our approach is to iteratively refine Apex based on lessons learned from as diverse a set of applications as possible. Many applications have been developed by users outside the core development team including engineers, researchers, and students. Usability is thus a central concern for every aspect of Apex visible to a user, including PDL, Sherpa, the Apex installation process, APIs, and user documentation. Apex users vary in their areas of expertise and in their familiarity with autonomy technology. Focusing on usability, a development philosophy summarized by the project motto "Usable Autonomy," has been important part of enabling diverse users to employ Apex successfully and to provide feedback needed to guide iterative, user-centered refinement.

Freed, Michael A.↗
NASA NTRS2010

Support for Systematic Code Reviews with the SCRUB Tool

SCRUB is a code review tool that supports both large, team-based software development efforts (e.g., for mission software) as well as individual tasks. The tool was developed at JPL to support a new, streamlined code review process that combines human-generated review reports with program-generated review reports from a customizable range of state-of-the-art source code analyzers. The leading commercial tools include Codesonar, Coverity, and Klocwork, each of which can achieve a reasonably low rate of false-positives in the warnings that they generate. The time required to analyze code with these tools can vary greatly. In each case, however, the tools produce results that would be difficult to realize with human code inspections alone. There is little overlap in the results produced by the different analyzers, and each analyzer used generally increases the effectiveness of the overall effort. The SCRUB tool allows all reports to be accessed through a single, uniform interface (see figure) that facilitates brows ing code and reports. Improvements over existing software include significant simplification, and leveraging of a range of commercial, static source code analyzers in a single, uniform framework. The tool runs as a small stand-alone application, avoiding the security problems related to tools based on Web browsers. A developer or reviewer, for instance, must have already obtained access rights to a code base before that code can be browsed and reviewed with the SCRUB tool. The tool cannot open any files or folders to which the user does not already have access. This means that the tool does not need to enforce or administer any additional security policies. The analysis results presented through the SCRUB tool s user interface are always computed off-line, given that, especially for larger projects, this computation can take longer than appropriate for interactive tool use. The recommended code review process that is supported by the SCRUB tool consists of three phases: Code Review, Developer Response, and Closeout Resolution. In the Code Review phase, all tool-based analysis reports are generated, and specific comments from expert code reviewers are entered into the SCRUB tool. In the second phase, Developer Response, the developer is asked to respond to each comment and tool-report that was produced, either agreeing or disagreeing to provide a fix that addresses the issue that was raised. In the third phase, Closeout Resolution, all disagreements are discussed in a meeting of all parties involved, and a resolution is made for all disagreements. The first two phases generally take one week each, and the third phase is concluded in a single closeout meeting.

Holzmann, Gerald J.↗
NASA NTRSDate not supplied

Harnessing Artificial Intelligence for Medical Diagnosis and Treatment During Space Exploration Missions

BACKGROUND The medical capabilities necessary for long-duration exploration missions (LDEMs) will differ tremendously from those currently available to crew medical officers (CMOs) on the International Space Station (ISS). Ground support will be more challenging due to distance-related communication delays and data transmission, and resource utilization must be optimized given limited ability for resupply. Clinical decision support systems (CDSSs) can help mitigate these limitations. The recent launch of generative artificial intelligence (AI) tools based upon large language models (LLM) support the creation of a smart assistant for onboard triage, diagnosis, and guided treatment of medical conditions during these missions. The Informing Mission Planning via Analysis of Complex Tradespaces (IMPACT) tool can help predict which clinical problems and outcomes are likely to occur for a design reference mission (DRM) and assist Medical Operations and systems engineering teams in creating a medical system that may optimally mitigate the predicted risks. The purpose of this study was to identify AI tools currently available or in development for the assistive diagnosis and care of medical conditions predicted for an extended duration Lunar mission. METHODS The 119 medical conditions currently built into the IMPACT suite were categorized into systems, and these diagnoses were used as keywords for our literature search. Using PubMed and Google Scholar, we performed a literature survey of AI tools applicable to these conditions. Article inclusion criteria included publication between the years 2017-2023, as the sentinel paper discussing the “selective attention” driving ChatGPT and other generative transformer models was published in June 2017. Where applicable, we reviewed only the top 1000 research articles (based on relevance) for each of the keywords/phrases. AI tools whose training sets were exclusive to a pediatric patient population were excluded. We also excluded any medical diagnostic tools (such as CT, MRI, mass spectrometry) or procedures (such as endoscopy, surgery) that are unlikely to be available during LDEMs due to mass and volume constraints, CMO knowledge, skills, and abilities, and/or inherent procedural risks. RESULTS Our survey highlighted several AI-driven tools for the triage, diagnosis, and management of those medical conditions highlighted by IMPACT. Selected publications for each medical condition were then screened for inclusion within ten systems-based categories including: general diagnostic tools (25), tools to diagnose and manage respiratory (40), dermatologic (34), neurologic (28), auditory and vestibular (30), ophthalmic (34), musculoskeletal (104), infection-associated (92), and gynecologic (19) conditions, as well as tools that could be deployed in the setting of trauma and emergency (34). CONCLUSIONS Numerous AI-driven tools were highlighted within this literature survey, ranging from chatbot assistants that triage knee pain to vision transformer models for diagnosis of ophthalmic conditions using ocular surface images captured with a mobile phone. Remaining challenges include optimizing connectivity and integration of existing and developing systems into the vehicles or habitats. Notably, findings from this survey could help guide the initial design of an all-encompassing, onboard medical AI assistant for use during future LDEMs.

R A Lacinski↗
NASA NTRSDate not supplied

Determining the Most Influencing Medical Conditions in MEDPRAT’s SIN Directed Graph

INTRODUCTION: The Susceptibility Inference Network (SIN) is a network of medical conditions, part of the Medical Extensible Probabilistic Risk Assessment Tool (MEDPRAT) developed by NASA to assess human health and medical risk to space exploration missions. The SIN is subject matter expert informed and acts as a prototype that provides relationships and dependencies between events modeled by MEDPRAT. Each vertex in the SIN has a weight which evaluates the severity of having the condition regardless of the progression from or to that condition. In this presentation, we consider two statistics to measure that stand alone risk: Quality Time Lost (QTL) and Loss of Crew Life (LOCL). Our goal is to identify the medical conditions that contribute the most to crew members QTL and LOCL risks due to progression of conditions in the network. We investigate how different computation parameters result in different condition rankings and address the choice of parameters that allows appropriate interventions to ensure space mission success. METHODS: The Katz score, one of many centrality measures created for ranking purposes in network analysis, takes into account all possible walks through the network, penalizing each additional step in a walk by a factor α called the Katz parameter. The literature does not provide specific values for the choice of α. We derive an analytical relationship between α and the maximum path length which has influence on the Katz score and ranking. Based on the probability of progression of each condition in the SIN, we identify that maximum path length of interest and calculate α that is then used in the Katz formula to rank the conditions in the SIN. RESULTS AND CONCLUSION: The effective probabilities of the SIN matrix generally fall below 10−6, which is below the level of the least influencing condition in the set. This corresponds to the probability of at most six consecutive progressions of a condition. Consequently, we calculate the Katz Parameter α and get 0.32. We rank the medical conditions and find that Acute Radiation Symptom is the condition the most prone to contribute to quality time loss due to progression.

risk analysis↗
NASA NTRS2003

Using Bond Graphs for Articulated, Flexible Multi-bodies, Sensors, Actuators, and Controllers with Application to the International Space Station

Conceptually, modeling of flexible, multi-body systems involves a formulation as a set of time-dependent partial differential equations. However, for practical, engineering purposes, this modeling is usually done using the method of Finite Elements, which approximates the set of partial differential equations, thus generalizing the approach to all continuous media. This research investigates the links between the Bond Graph method and the classical methods used to develop system models and advocates the Bond Graph Methodology and current bond graph tools as alternate approaches that will lead to a quick and precise understanding of a flexible multi-body system under automatic control. For long endurance, complex spacecraft, because of articulation and mission evolution the model of the physical system may change frequently. So a method of automatic generation and regeneration of system models that does not lead to implicit equations, as does the Lagrange equation approach, is desirable. The bond graph method has been shown to be amenable to automatic generation of equations with appropriate consideration of causality. Indeed human-interactive software now exists that automatically generates both symbolic and numeric system models and evaluates causality as the user develops the model, e.g. the CAMP-G software package. In this paper the CAMP-G package is used to generate a bond graph model of the International Space Station (ISS) at an early stage in its assembly, Zvezda. The ISS is an ideal example because it is a collection of bodies that are articulated, many of which are highly flexible. Also many reaction jets are used to control translation and attitude, and many electric motors are used to articulate appendages, which consist of photovoltaic arrays and composite assemblies. The Zvezda bond graph model is compared to an existing model, which was generated by the NASA Johnson Space Center during the Verification and Analysis Cycle of Zvezda.

Montgomery, Raymond C.↗