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Multi-Platform Avionics Simulator

Multi-Platform Avionics Simulator (MPAvSim) is a software library for development of simulations of avionic hardware. MPAvSim facilitates simulation of interactions between flight software and such avionic peripheral equipment as telecommunication devices, thrusters, pyrotechnic devices, motor controllers, and scientific instruments. MPAvSim focuses on the behavior of avionics as seen by flight software, rather than on performing high-fidelity simulations of dynamics. However, MPAvSim is easily integrable with other programs that do perform such simulations. MPAvSim makes it possible to do real-time partial hardware- in-the-loop simulations. An MPAvSim simulation consists of execution chains (see figure) represented by flow graphs of models, defined here as stateless procedures that do some work. During a simulation, MPAvSim walks the execution chain, running each model in turn. Using MPAvSim, flight software can be run against a spacecraft that is all simulation, all hardware, or part hardware and part simulation. With respect to a specific piece of hardware, either the hardware itself or its simulation can be plugged in without affecting the rest of the system. Thus, flight software can be tested before hardware is available, and as items of hardware become available, they can be substituted for their simulations, with minimal disruption.

Clark, Micah↗

A Reference Model for Software and System Inspections. White Paper

Software Quality Assurance (SQA) is an important component of the software development process. SQA processes provide assurance that the software products and processes in the project life cycle conform to their specified requirements by planning, enacting, and performing a set of activities to provide adequate confidence that quality is being built into the software. Typical techniques include: (1) Testing (2) Simulation (3) Model checking (4) Symbolic execution (5) Management reviews (6) Technical reviews (7) Inspections (8) Walk-throughs (9) Audits (10) Analysis (complexity analysis, control flow analysis, algorithmic analysis) (11) Formal method Our work over the last few years has resulted in substantial knowledge about SQA techniques, especially the areas of technical reviews and inspections. But can we apply the same QA techniques to the system development process? If yes, what kind of tailoring do we need before applying them in the system engineering context? If not, what types of QA techniques are actually used at system level? And, is there any room for improvement.) After a brief examination of the system engineering literature (especially focused on NASA and DoD guidance) we found that: (1) System and software development process interact with each other at different phases through development life cycle (2) Reviews are emphasized in both system and software development. (Figl.3). For some reviews (e.g. SRR, PDR, CDR), there are both system versions and software versions. (3) Analysis techniques are emphasized (e.g. Fault Tree Analysis, Preliminary Hazard Analysis) and some details are given about how to apply them. (4) Reviews are expected to use the outputs of the analysis techniques. In other words, these particular analyses are usually conducted in preparation for (before) reviews. The goal of our work is to explore the interaction between the Quality Assurance (QA) techniques at the system level and the software level.

He, Lulu↗

The Importance of HRA in Human Space Flight: Understanding the Risks

Human performance is critical to crew safety during space missions. Humans interact with hardware and software during ground processing, normal flight, and in response to events. Human interactions with hardware and software can cause Loss of Crew and/or Vehicle (LOCV) through improper actions, or may prevent LOCV through recovery and control actions. Humans have the ability to deal with complex situations and system interactions beyond the capability of machines. Human Reliability Analysis (HRA) is a method used to qualitatively and quantitatively assess the occurrence of human failures that affect availability and reliability of complex systems. Modeling human actions with their corresponding failure probabilities in a Probabilistic Risk Assessment (PRA) provides a more complete picture of system risks and risk contributions. A high-quality HRA can provide valuable information on potential areas for improvement, including training, procedures, human interfaces design, and the need for automation. Modeling human error has always been a challenge in part because performance data is not always readily available. For spaceflight, the challenge is amplified not only because of the small number of participants and limited amount of performance data available, but also due to the lack of definition of the unique factors influencing human performance in space. These factors, called performance shaping factors in HRA terminology, are used in HRA techniques to modify basic human error probabilities in order to capture the context of an analyzed task. Many of the human error modeling techniques were developed within the context of nuclear power plants and therefore the methodologies do not address spaceflight factors such as the effects of microgravity and longer duration missions. This presentation will describe the types of human error risks which have shown up as risk drivers in the Shuttle PRA which may be applicable to commercial space flight. As with other large PRAs of complex machines, human error in the Shuttle PRA proved to be an important contributor (~12 percent) to LOCV. An existing HRA technique was adapted for use in the Shuttle PRA, but additional guidance and improvements are needed to make the HRA task in space-related PRAs easier and more accurate. Therefore, this presentation will also outline plans for expanding current HRA methodology to more explicitly cover spaceflight performance shaping factors.

Hamlin, Teri↗

Software-Engineering Process Simulation (SEPS) model

The Software Engineering Process Simulation (SEPS) model is described which was developed at JPL. SEPS is a dynamic simulation model of the software project development process. It uses the feedback principles of system dynamics to simulate the dynamic interactions among various software life cycle development activities and management decision making processes. The model is designed to be a planning tool to examine tradeoffs of cost, schedule, and functionality, and to test the implications of different managerial policies on a project's outcome. Furthermore, SEPS will enable software managers to gain a better understanding of the dynamics of software project development and perform postmodern assessments.

Lin, C. Y.↗

Space station: The role of software

Software will play a critical role throughout the Space Station Program. This presentation sets the stage and prompts participant interaction at the Software Issues Forum. The presentation is structured into three major topics: (1) an overview of the concept and status of the Space Station Program; (2) several charts designed to lay out the scope and role of software; and (3) information addressing the four specific areas selected for focus at the forum, specifically: software management, the software development environment, languages, and standards. NASA's current thinking is highlighted and some of the relevant critical issues are raised.

Hall, D.↗

An experiment with interactive planning models

Experiments on decision making in planning problems are described. Executives were tested in dealing with capital investments and competitive pricing decisions under conditions of uncertainty. A software package, the interactive risk analysis model system, was developed, and two controlled experiments were conducted. It is concluded that planning models can aid management, and predicted uses of the models are as a central tool, as an educational tool, to improve consistency in decision making, to improve communications, and as a tool for consensus decision making.

Beville, J.↗

A new method for hardware/software integration of strategic systems Case study for the Space Shuttle

A new method for ground testing a complex avionics system in an integrated manner has been developed. A case study for the Space Shuttle, on which the concept has been successfully implemented, is described here. This approach utilizes the actual hardware and software of the vehicle to perform a realistic simulation of its mission, verifying in the process all the critical interfaces and interactions of the software with the hardware. The advantages over current testing techniques are discussed, as well as the extension of the concept to other strategic systems.

Ionescu, T. V.↗

NASA Software Engineering Benchmarking Study

To identify best practices for the improvement of software engineering on projects, NASA's Offices of Chief Engineer (OCE) and Safety and Mission Assurance (OSMA) formed a team led by Heather Rarick and Sally Godfrey to conduct this benchmarking study. The primary goals of the study are to identify best practices that: Improve the management and technical development of software intensive systems; Have a track record of successful deployment by aerospace industries, universities [including research and development (R&D) laboratories], and defense services, as well as NASA's own component Centers; and Identify candidate solutions for NASA's software issues. Beginning in the late fall of 2010, focus topics were chosen and interview questions were developed, based on the NASA top software challenges. Between February 2011 and November 2011, the Benchmark Team interviewed a total of 18 organizations, consisting of five NASA Centers, five industry organizations, four defense services organizations, and four university or university R and D laboratory organizations. A software assurance representative also participated in each of the interviews to focus on assurance and software safety best practices. Interviewees provided a wealth of information on each topic area that included: software policy, software acquisition, software assurance, testing, training, maintaining rigor in small projects, metrics, and use of the Capability Maturity Model Integration (CMMI) framework, as well as a number of special topics that came up in the discussions. NASA's software engineering practices compared favorably with the external organizations in most benchmark areas, but in every topic, there were ways in which NASA could improve its practices. Compared to defense services organizations and some of the industry organizations, one of NASA's notable weaknesses involved communication with contractors regarding its policies and requirements for acquired software. One of NASA's strengths was its software assurance practices, which seemed to rate well in comparison to the other organizational groups and also seemed to include a larger scope of activities. An unexpected benefit of the software benchmarking study was the identification of many opportunities for collaboration in areas including metrics, training, sharing of CMMI experiences and resources such as instructors and CMMI Lead Appraisers, and even sharing of assets such as documented processes. A further unexpected benefit of the study was the feedback on NASA practices that was received from some of the organizations interviewed. From that feedback, other potential areas where NASA could improve were highlighted, such as accuracy of software cost estimation and budgetary practices. The detailed report contains discussion of the practices noted in each of the topic areas, as well as a summary of observations and recommendations from each of the topic areas. The resulting 24 recommendations from the topic areas were then consolidated to eliminate duplication and culled into a set of 14 suggested actionable recommendations. This final set of actionable recommendations, listed below, are items that can be implemented to improve NASA's software engineering practices and to help address many of the items that were listed in the NASA top software engineering issues. 1. Develop and implement standard contract language for software procurements. 2. Advance accurate and trusted software cost estimates for both procured and in-house software and improve the capture of actual cost data to facilitate further improvements. 3. Establish a consistent set of objectives and expectations, specifically types of metrics at the Agency level, so key trends and models can be identified and used to continuously improve software processes and each software development effort. 4. Maintain the CMMI Maturity Level requirement for critical NASA projects and use CMMI to measure organizations developing software for NASA. 5.onsolidate, collect and, if needed, develop common processes principles and other assets across the Agency in order to provide more consistency in software development and acquisition practices and to reduce the overall cost of maintaining or increasing current NASA CMMI maturity levels. 6. Provide additional support for small projects that includes: (a) guidance for appropriate tailoring of requirements for small projects, (b) availability of suitable tools, including support tool set-up and training, and (c) training for small project personnel, assurance personnel and technical authorities on the acceptable options for tailoring requirements and performing assurance on small projects. 7. Develop software training classes for the more experienced software engineers using on-line training, videos, or small separate modules of training that can be accommodated as needed throughout a project. 8. Create guidelines to structure non-classroom training opportunities such as mentoring, peer reviews, lessons learned sessions, and on-the-job training. 9. Develop a set of predictive software defect data and a process for assessing software testing metric data against it. 10. Assess Agency-wide licenses for commonly used software tools. 11. Fill the knowledge gap in common software engineering practices for new hires and co-ops.12. Work through the Science, Technology, Engineering and Mathematics (STEM) program with universities in strengthening education in the use of common software engineering practices and standards. 13. Follow up this benchmark study with a deeper look into what both internal and external organizations perceive as the scope of software assurance, the value they expect to obtain from it, and the shortcomings they experience in the current practice. 14. Continue interactions with external software engineering environment through collaborations, knowledge sharing, and benchmarking.

Rarick, Heather L.↗

IRAS software analysis library

The goal of this project was to collect 'research software' written in Interactive Data Language (IDL) to support analysis of data from the Infrared Astronomical Satellite (IRAS) and make it available to the larger community. 'Research Software' describes software created by researchers and staff for a specific research goal, but lacks sufficient documentation, easy to use interfaces, and rigorous debugging. Additionally, most of the IDL/IRAS code available needed to be ported to a (largely) hardware independent new version of IDL.

Domik, Gitta↗

Real-Time Data Display

RT-Display is a MATLAB-based data acquisition environment designed to use a variety of commercial off-the-shelf (COTS) hardware to digitize analog signals to a standard data format usable by other post-acquisition data analysis tools. This software presents the acquired data in real time using a variety of signal-processing algorithms. The acquired data is stored in a standard Operator Interactive Signal Processing Software (OISPS) data-formatted file. RT-Display is primarily configured to use the Agilent VXI (or equivalent) data acquisition boards used in such systems as MIDDAS (Multi-channel Integrated Dynamic Data Acquisition System). The software is generalized and deployable in almost any testing environment, without limitations or proprietary configuration for a specific test program or project. With the Agilent hardware configured and in place, users can start the program and, in one step, immediately begin digitizing multiple channels of data. Once the acquisition is completed, data is converted into a common binary format that also can be translated to specific formats used by external analysis software, such as OISPS and PC-Signal (product of AI Signal Research Inc.). RT-Display at the time of this reporting was certified on Agilent hardware capable of acquisition up to 196,608 samples per second. Data signals are presented to the user on-screen simultaneously for 16 channels. Each channel can be viewed individually, with a maximum capability of 160 signal channels (depending on hardware configuration). Current signal presentations include: time data, fast Fourier transforms (FFT), and power spectral density plots (PSD). Additional processing algorithms can be easily incorporated into this environment.

Pedings, Marc↗

Software for Automation of Real-Time Agents, Version 2

Version 2 of Closed Loop Execution and Recovery (CLEaR) has been developed. CLEaR is an artificial intelligence computer program for use in planning and execution of actions of autonomous agents, including, for example, Deep Space Network (DSN) antenna ground stations, robotic exploratory ground vehicles (rovers), robotic aircraft (UAVs), and robotic spacecraft. CLEaR automates the generation and execution of command sequences, monitoring the sequence execution, and modifying the command sequence in response to execution deviations and failures as well as new goals for the agent to achieve. The development of CLEaR has focused on the unification of planning and execution to increase the ability of the autonomous agent to perform under tight resource and time constraints coupled with uncertainty in how much of resources and time will be required to perform a task. This unification is realized by extending the traditional three-tier robotic control architecture by increasing the interaction between the software components that perform deliberation and reactive functions. The increase in interaction reduces the need to replan, enables earlier detection of the need to replan, and enables replanning to occur before an agent enters a state of failure.

Fisher, Forest↗

Rapid Response Risk Assessment in New Project Development

A capability for rapidly performing quantitative risk assessments has been developed by JSC Safety and Mission Assurance for use on project design trade studies early in the project life cycle, i.e., concept development through preliminary design phases. A risk assessment tool set has been developed consisting of interactive and integrated software modules that allow a user/project designer to assess the impact of alternative design or programmatic options on the probability of mission success or other risk metrics. The risk and design trade space includes interactive options for selecting parameters and/or metrics for numerous design characteristics including component reliability characteristics, functional redundancy levels, item or system technology readiness levels, and mission event characteristics. This capability is intended for use on any project or system development with a defined mission, and an example project will used for demonstration and descriptive purposes, e.g., landing a robot on the moon. The effects of various alternative design considerations and their impact of these decisions on mission success (or failure) can be measured in real time on a personal computer. This capability provides a high degree of efficiency for quickly providing information in NASA s evolving risk-based decision environment

Graber, Robert R.↗

Running SINDA '85/FLUINT interactive on the VAX

Computer software as engineering tools are typically run in three modes: Batch, Demand, and Interactive. The first two are the most popular in the SINDA world. The third one is not so popular, due probably to the users inaccessibility to the command procedure files for running SINDA '85, or lack of familiarity with the SINDA '85 execution processes (pre-processor, processor, compilation, linking, execution and all of the file assignment, creation, deletions and de-assignments). Interactive is the mode that makes thermal analysis with SINDA '85 a real-time design tool. This paper explains a command procedure sufficient (the minimum modifications required in an existing demand command procedure) to run SINDA '85 on the VAX in an interactive mode. To exercise the procedure a sample problem is presented exemplifying the mode, plus additional programming capabilities available in SINDA '85. Following the same guidelines the process can be extended to other SINDA '85 residence computer platforms.

Simmonds, Boris↗

Managing Complexity in the MSL/Curiosity Entry, Descent, and Landing Flight Software and Avionics Verification and Validation Campaign

The complexity of the Mars Science Laboratory (MSL) mission presented the Entry, Descent, and Landing systems engineering team with many challenges in its Verification and Validation (V&V) campaign. This paper describes some of the logistical hurdles related to managing a complex set of requirements, test venues, test objectives, and analysis products in the implementation of a specific portion of the overall V&V program to test the interaction of flight software with the MSL avionics suite. Application-specific solutions to these problems are presented herein, which can be generalized to other space missions and to similar formidable systems engineering problems.

Stehura, Aaron↗

Evaluation of Early Ground Control Station Configurations for Interacting with a UAS Traffic Management (UTM) System

The purpose of this paper is to report on a human factors evaluation of ground control station design concepts for interacting with an unmanned traffic management system. The data collected for this paper comes from recent field tests for NASA's Unmanned Traffic Management (UTM) project, and covers the following topics; workload, situation awareness, as well as flight crew communication, coordination, and procedures. The goal of this evaluation was to determine if the various software implementations for interacting with the UTM system can be described and classified into design concepts to provide guidance for the development of future UTM interfaces. We begin with a brief description of NASA's UTM project, followed by a description of the test range configuration related to a second development phase. We identified (post hoc) two classes in which the ground control stations could be grouped. This grouping was based on level of display integration. The analysis was exploratory and informal. It was conducted to compare ground stations across those two classes and against the aforementioned topics. Herein, we discuss the results.

unmanned traffic management↗

Realtime Three-Dimensional Simulation

Real-time three-dimensional simulations are dependent of three areas: databases and models (3D geometric polygon structure, multiple levels of detail, sound sample waveforms, optimized for interactive, real time use); software applications (software program that controls input devices, visual channels, scene objects, interaction, collision detection, special effects, time of day, weather, I/O, and communication); and hardware (computer, sound processor, monitors control sticks, position trackers, head-mounted displays, amplifiers, speakers, and communications.

Ramsdell, Craig↗

Enhancements to the GRIDGEN structured grid generation system for internal and external flow applications

GRIDGEN is a government domain software package for interactive generation of multiple block grids around general configurations. Though it has been freely available since 1989, it has not been widely embraced by the internal flow community due to a misconception that it was designed for external flow use only. In reality GRIDGEN has always worked for internal flow applications, and GRIDGEN ongoing enhancements are increasing the quality of and efficiency with which grids for external and internal flow problems may be constructed. The software consists of four codes used to perform the four steps of the grid generation process. GRIDBLOCK is first used to decompose the flow domain into a collection of component blocks and then to establish interblock connections and flow solver boundary conditions. GRIDGEN2D is then used to generate surface grids on the outer shell of each component block. GRIDGEN3D generates grid points on the interior of each block, and finally GRIDVUE3D is used to inspect the resulting multiple block grid. Three of these codes (GRIDBLOCK, GRIDGEN2D, and GRIDVUE3D) are highly interactive and graphical in nature, and currently run on Silicon Graphics, Inc., and IBM RS/6000 workstations. The lone batch code (GRIDGEN3D) may be run on any of several Unix based platforms. Surface grid generation in GRIDGEN2D is being improved with the addition of higher order surface definitions (NURBS and parametric surfaces input in IGES format and bicubic surfaces input in PATRAN Neutral File format) and double precision mathematics. In addition, two types of automation have been added to GRIDGEN2D that reduce the learning curve slope for new users and eliminate work for experienced users. Volume grid generation using GRIDGEN3D has been improved via the addition of an advanced hybrid control function formulation that provides both orthogonality and clustering control at the block faces and clustering control on the block interior.

Steinbrenner, John P.↗

A Uniform Ontology for Software Interfaces

It is universally the case that computer users who are not also computer specialists prefer to deal with computers' in terms of a familiar ontology, namely that of their application domains. For example, the well-known Windows ontology assumes that the user is an office worker, and therefore should be presented with a "desktop environment" featuring entities such as (virtual) file folders, documents, appointment calendars, and the like, rather than a world of machine registers and machine language instructions, or even the DOS command level. The central theme of this research has been the proposition that the user interacting with a software system should have at his disposal both the ontology underlying the system, as well as a model of the system. This information is necessary for the understanding of the system in use, as well as for the automatic generation of assistance for the user, both in solving the problem for which the application is designed, and for providing guidance in the capabilities and use of the system.

Feyock, Stefan↗