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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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At least 541 records · Page 30
All sourcesNASA NTRSDOE OSTI
NASA NTRS1978

Tools for Embedded Computing Systems Software

A workshop was held to assess the state of tools for embedded systems software and to determine directions for tool development. A synopsis of the talk and the key figures of each workshop presentation, together with chairmen summaries, are presented. The presentations covered four major areas: (1) tools and the software environment (development and testing); (2) tools and software requirements, design, and specification; (3) tools and language processors; and (4) tools and verification and validation (analysis and testing). The utility and contribution of existing tools and research results for the development and testing of embedded computing systems software are described and assessed.

Source record↗
NASA NTRS1983

Simulations used in the development and flight test of the HiMAT vehicle

Real-time simulations have been essential in the flight-test program of the highly maneuverable aircraft technology (HiMAT) remotely piloted research vehicle at the Dryden Flight Research Facility of NASA Ames Research Center. The HiMAT project makes extensive use of simulations in design, development, and qualification for flight, pilot training, and flight planning. Four distinct simulations, each with varying amounts of hardware in the loop, were developed for the HiMAT project. The use of simulations has been the key to flight qualification of the HiMAT vehicle. Specifically, they are useful in detecting anomalous behavior of the flight software and hardware at the various stages of development, verification, and validation.

Evans, M. B.↗
NASA NTRS1984

The role of simulation in the development and flight test of the HiMAT vehicle

Real time simulations have been essential in the flight test program of the highly maneuverable aircraft technology (HiMAT) remotely piloted research vehicle at NASA Ames Research Center's Dryden Flight Research Facility. The HiMAT project makes extensive use of simulations in design, development, and qualification for flight, pilot training, and flight planning. Four distinct simulations, each with varying amounts of hardware in the loop, were developed for the HiMAT project. The use of simulations in detecting anomalous behavior of the flight software and hardware at the various stages of development, verification, and validation has been the key to flight qualification of the HiMAT vehicle.

Evans, M. B.↗
NASA NTRS1989

Modifying high-order aeroelastic math model of a jet transport using maximum likelihood estimation

The design of control laws to damp flexible structural modes requires accurate math models. Unlike the design of control laws for rigid body motion (e.g., where robust control is used to compensate for modeling inaccuracies), structural mode damping usually employs narrow band notch filters. In order to obtain the required accuracy in the math model, maximum likelihood estimation technique is employed to improve the accuracy of the math model using flight data. Presented here are all phases of this methodology: (1) pre-flight analysis (i.e., optimal input signal design for flight test, sensor location determination, model reduction technique, etc.), (2) data collection and preprocessing, and (3) post-flight analysis (i.e., estimation technique and model verification). In addition, a discussion is presented of the software tools used and the need for future study in this field.

Anissipour, Amir A.↗
NASA NTRS1990

GCS plan for software aspects of certification

As part of the Guidance and Control Software (GCS) research project being sponsored by NASA to evaluate the failure processes of software, standard industry software development procedures are being employed. To ensure that these procedures are authentic, the guidelines outlined in the Radio Technical Commission for Aeronautics (RTCA/DO-178A document entitled, software considerations in airborne systems and equipment certification, were adopted. A major aspect of these guidelines is proper documentation. As such, this report, the plan for software aspects of certification, was produced in accordance with DO-178A. An overview is given of the GCS research project, including the goals of the project, project organization, and project schedules. It also specifies the plans for all aspects of the project which relate to the certification of the GCS implementations developed under a NASA contract. These plans include decisions made regarding the software specification, accuracy requirements, configuration management, implementation development and verification, and the development of the GCS simulator.

Shagnea, Anita M.↗
NASA NTRS1994

The PLAID graphics analysis impact on the space program

An ongoing project design often requires visual verification at various stages. These requirements are critically important because the subsequent phases of that project might depend on the complete verification of a particular stage. Currently, there are several software packages at JSC that provide such simulation capabilities. We present the simulation capabilities of the PLAID modeling system used in the Flight Crew Support Division for human factors analyses. We summarize some ongoing studies in kinematics, lighting, EVA activities, and discuss various applications in the mission planning of the current Space Shuttle flights and the assembly sequence of the Space Station Freedom with emphasis on the redesign effort.

Nguyen, Jennifer P.↗
NASA NTRS2009

Verification and Validation of Adaptive and Intelligent Systems with Flight Test Results

F-15 IFCS project goals are: a) Demonstrate Control Approaches that can Efficiently Optimize Aircraft Performance in both Normal and Failure Conditions [A] & [B] failures. b) Advance Neural Network-Based Flight Control Technology for New Aerospace Systems Designs with a Pilot in the Loop. Gen II objectives include; a) Implement and Fly a Direct Adaptive Neural Network Based Flight Controller; b) Demonstrate the Ability of the System to Adapt to Simulated System Failures: 1) Suppress Transients Associated with Failure; 2) Re-Establish Sufficient Control and Handling of Vehicle for Safe Recovery. c) Provide Flight Experience for Development of Verification and Validation Processes for Flight Critical Neural Network Software.

Burken, John J.↗
NASA NTRS2009

Verifying Architectural Design Rules of the Flight Software Product Line

This paper presents experiences of verifying architectural design rules of the NASA Core Flight Software (CFS) product line implementation. The goal of the verification is to check whether the implementation is consistent with the CFS architectural rules derived from the developer's guide. The results indicate that consistency checking helps a) identifying architecturally significant deviations that were eluded during code reviews, b) clarifying the design rules to the team, and c) assessing the overall implementation quality. Furthermore, it helps connecting business goals to architectural principles, and to the implementation. This paper is the first step in the definition of a method for analyzing and evaluating product line implementations from an architecture-centric perspective.

Ganesan, Dharmalingam↗
NASA NTRS2010

TEAMS Model Analyzer

The TEAMS model analyzer is a supporting tool developed to work with models created with TEAMS (Testability, Engineering, and Maintenance System), which was developed by QSI. In an effort to reduce the time spent in the manual process that each TEAMS modeler must perform in the preparation of reporting for model reviews, a new tool has been developed as an aid to models developed in TEAMS. The software allows for the viewing, reporting, and checking of TEAMS models that are checked into the TEAMS model database. The software allows the user to selectively model in a hierarchical tree outline view that displays the components, failure modes, and ports. The reporting features allow the user to quickly gather statistics about the model, and generate an input/output report pertaining to all of the components. Rules can be automatically validated against the model, with a report generated containing resulting inconsistencies. In addition to reducing manual effort, this software also provides an automated process framework for the Verification and Validation (V&V) effort that will follow development of these models. The aid of such an automated tool would have a significant impact on the V&V process.

Tijidjian, Raffi P.↗
NASA NTRSDate not supplied

Understanding and Verifying Neural Networks

Deep Neural Networks (DNNs) have gained immense popularity in recent times and have widespread use in applications such as image classification, sentiment analysis, speech recognition and also in safety-critical applications such as autonomous driving. However, they suffer limitations such as lack of explainability and robustness which raise safety and security concerns in their usage. Further, the complex structure and large input spaces of DNNs act as an impediment to thorough verification and testing. The SafeDNN project at the Robust Software Engineering (RSE) group at NASA aims at exploring techniques to ensure that systems that use deep neural networks are safe, robust and interpretable. In this talk, I will be presenting our technique Prophecy that automatically infers formal properties of deep neural network models. The tool extracts patterns based on neuron activations as preconditions that imply certain desirable output properties of the model. I would be highlighting case studies that use Prophecy in obtaining explanations for network decisions, understanding correct and incorrect behavior, providing formal guarantees wrt safety and robustness, and debugging neural network models. We have applied the tool on image classification networks, neural network controllers providing turn advisories in unmanned aircrafts, regression models used for autonomous center-line tracking in aircrafts and neural network object detectors

Deep Neural Networks↗
NASA NTRS2014

Evolution of Software-Only-Simulation at NASA IV and V

Software-Only-Simulations have been an emerging but quickly developing field of study throughout NASA. The NASA Independent Verification Validation (IVV) Independent Test Capability (ITC) team has been rapidly building a collection of simulators for a wide range of NASA missions. ITC specializes in full end-to-end simulations that enable developers, VV personnel, and operators to test-as-you-fly. In four years, the team has delivered a wide variety of spacecraft simulations that have ranged from low complexity science missions such as the Global Precipitation Management (GPM) satellite and the Deep Space Climate Observatory (DSCOVR), to the extremely complex missions such as the James Webb Space Telescope (JWST) and Space Launch System (SLS).This paper describes the evolution of ITCs technologies and processes that have been utilized to design, implement, and deploy end-to-end simulation environments for various NASA missions. A comparison of mission simulators are discussed with focus on technology and lessons learned in complexity, hardware modeling, and continuous integration. The paper also describes the methods for executing the missions unmodified flight software binaries (not cross-compiled) for verification and validation activities.

Embedded↗
NASA NTRS1981

Management of the Galileo attitude and articulation control flight software development

Management concepts are presented for software development for a new technology area, i.e., real-time autonomous, computer-based spacecraft control. Flight computer selection and sizing are done initially to maximize performance within constraints of size, power, and cost. A higher order language is chosen to enhance productivity. Because the computer is embedded in the control systems hardware and is tied to the iterative design process of the spacecraft, the management and configuration control of the software is different from more typical applications. The development process must permit early coding but accept late changes. Margin management must be a continuing process in the development. Validation and verification is a special problem because it is not feasible to test the software in the actual operating environment prior to launch.

Pace, G. D.↗
NASA NTRS1990

Automation of the Environmental Control and Life Support System

The objective of the Environmental Control and Life Support System (ECLSS) Advanced Automation Project is to recommend and develop advanced software for the initial and evolutionary Space Station Freedom (SSF) ECLS system which will minimize the crew and ground manpower needed for operations. Another objective includes capturing ECLSS design and development knowledge for future missions. This report summarizes our results from Phase I, the ECLSS domain analysis phase, which we broke down into three steps: 1) Analyze and document the baselined ECLS system, 2) envision as our goal an evolution to a fully automated regenerative life support system, built upon an augmented baseline, and 3) document the augmentations (hooks and scars) and advanced software systems which we see as necessary in achieving minimal manpower support for ECLSS operations. In addition, Phase I included development of an advanced software life cycle testing tools will be used in the development of the software. In this way, we plan in preparation for phase II and III, the development and integration phases, respectively. Automated knowledge acquisition, engineering, verification, and can capture ECLSS development knowledge for future use, develop more robust and complex software, provide feedback to the KBS tool community, and insure proper visibility of our efforts.

Dewberry, Brandon S.↗
NASA NTRSDate not supplied

An Integrated Development Environment for the Prototype Verification System

The steep learning curve of formal technologies is a well-known barrier to the adoption of formal verification tools in industry. This paper presents VSCode-PVS, a modern integrated development environment for the Prototype Verification System (PVS). This new environment integrates the editing and proof management functionalities of PVS in Visual Studio Code, a popular code editor widely used by software developers. VSCode-PVS provides functionalities that developers expect to find in modern verification tools but are not available in the standard Emacs front-end of PVS, such as auto-completion, point-and-click navigation of definitions, live diagnostics for errors, and literate programming. The main features and architecture of the environment are presented, along with a comparison with other similar tools.

Paolo Masci↗
NASA NTRS1977

Data processing system and interfacing elements time base analysis

The processing of time in the Orbiter System Services software and the associated facilities provided to the user community are described. The descriptions are directed toward showing the functional intent of the design rather than the actual implementation. Simplified flow diagrams are included. Based upon detailed analysis of a preliminary review copy of the Approach and Landing Test (ALT) System Software Detailed Design Specification and the Program Listings for Version 17 Prime, the processing of time has the potential for error free operations. The processing of time is not expected to change between ALT and the Operational Flight Test (OFT) other than differences in value of some constants for control and limit checking. Due to the dynamic nature of onboard time processing and its criticality to the successful operation of the orbiter, it is recommended that a comprehensive list of external variables, their locations, initial values, and a 'where used' listing be produced, as a by-product of the link edit process, for all non-HAL coding. In addition, a careful review of the verification test procedures for the System Services time-related software is recommended.

Blackburn, J. D.↗
NASA NTRS2016

A Generic Modeling Process to Support Functional Fault Model Development

Functional fault models (FFMs) are qualitative representations of a system's failure space that are used to provide a diagnostic of the modeled system. An FFM simulates the failure effect propagation paths within a system between failure modes and observation points. These models contain a significant amount of information about the system including the design, operation and off nominal behavior. The development and verification of the models can be costly in both time and resources. In addition, models depicting similar components can be distinct, both in appearance and function, when created individually, because there are numerous ways of representing the failure space within each component. Generic application of FFMs has the advantages of software code reuse: reduction of time and resources in both development and verification, and a standard set of component models from which future system models can be generated with common appearance and diagnostic performance. This paper outlines the motivation to develop a generic modeling process for FFMs at the component level and the effort to implement that process through modeling conventions and a software tool. The implementation of this generic modeling process within a fault isolation demonstration for NASA's Advanced Ground System Maintenance (AGSM) Integrated Health Management (IHM) project is presented and the impact discussed.

Design Analysis↗
NASA NTRS1995

Analysis/Design Tool

Excelerator II, developed by INTERSOLV, Inc., provides a complete environment for rules-based expert systems. The software incorporates NASA's C Language Integrated Production System (CLIPS), a shell for constructing expert systems. Excelerator II provides complex verification and transformation routines based on matching that is simple and inexpensive. *Excelerator II was sold to SELECT Software Tools in June 1997 and is now called SELECT Excelerator. SELECT has assumed full support and maintenance for the product line.

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