Engineering topics
Crues, Edwin Z.
Publications and source records attributed to Crues, Edwin Z..
Assessment of the Draft AIAA S-119 Flight Dynamic Model Exchange Standard
An assessment of a draft AIAA standard for flight dynamics model exchange, ANSI/AIAA S-119-2011, was conducted on behalf of NASA by a team from the NASA Engineering and Safety Center. The assessment included adding the capability of importing standard models into real-time simulation facilities at several NASA Centers as well as into analysis simulation tools. All participants were successful at importing two example models into their respective simulation frameworks by using existing software libraries or by writing new import tools. Deficiencies in the libraries and format documentation were identified and fixed; suggestions for improvements to the standard were provided to the AIAA. An innovative tool to generate C code directly from such a model was developed. Performance of the software libraries compared favorably with compiled code. As a result of this assessment, several NASA Centers can now import standard models directly into their simulations. NASA is considering adopting the now-published S-119 standard as an internal recommended practice.
An Orion/Ares I Launch and Ascent Simulation: One Segment of the Distributed Space Exploration Simulation (DSES)
This paper describes the architecture and implementation of a distributed launch and ascent simulation of NASA's Orion spacecraft and Ares I launch vehicle. This simulation is one segment of the Distributed Space Exploration Simulation (DSES) Project. The DSES project is a research and development collaboration between NASA centers which investigates technologies and processes for distributed simulation of complex space systems in support of NASA's Exploration Initiative. DSES is developing an integrated end-to-end simulation capability to support NASA development and deployment of new exploration spacecraft and missions. This paper describes the first in a collection of simulation capabilities that DSES will support.
A Coordinated Initialization Process for the Distributed Space Exploration Simulation
A viewgraph presentation on the federate initialization process for the Distributed Space Exploration Simulation (DSES) is described. The topics include: 1) Background: DSES; 2) Simulation requirements; 3) Nine Step Initialization; 4) Step 1: Create the Federation; 5) Step 2: Publish and Subscribe; 6) Step 3: Create Object Instances; 7) Step 4: Confirm All Federates Have Joined; 8) Step 5: Achieve initialize Synchronization Point; 9) Step 6: Update Object Instances With Initial Data; 10) Step 7: Wait for Object Reflections; 11) Step 8: Set Up Time Management; 12) Step 9: Achieve startup Synchronization Point; and 13) Conclusions
A Coordinated Initialization Process for the Distributed Space Exploration Simulation (DSES)
This document describes the federate initialization process that was developed at the NASA Johnson Space Center with the HIIA Transfer Vehicle Flight Controller Trainer (HTV FCT) simulations and refined in the Distributed Space Exploration Simulation (DSES). These simulations use the High Level Architecture (HLA) IEEE 1516 to provide the communication and coordination between the distributed parts of the simulation. The purpose of the paper is to describe a generic initialization sequence that can be used to create a federate that can: 1. Properly initialize all HLA objects, object instances, interactions, and time management 2. Check for the presence of all federates 3. Coordinate startup with other federates 4. Robustly initialize and share initial object instance data with other federates.
The Distributed Space Exploration Simulation (DSES)
The paper describes the Distributed Space Exploration Simulation (DSES) Project, a research and development collaboration between NASA centers which focuses on the investigation and development of technologies, processes and integrated simulations related to the collaborative distributed simulation of complex space systems in support of NASA's Exploration Initiative. This paper describes the three major components of DSES: network infrastructure, software infrastructure and simulation development. In the network work area, DSES is developing a Distributed Simulation Network that will provide agency wide support for distributed simulation between all NASA centers. In the software work area, DSES is developing a collection of software models, tool and procedures that ease the burden of developing distributed simulations and provides a consistent interoperability infrastructure for agency wide participation in integrated simulation. Finally, for simulation development, DSES is developing an integrated end-to-end simulation capability to support NASA development of new exploration spacecraft and missions. This paper will present current status and plans for each of these work areas with specific examples of simulations that support NASA's exploration initiatives.
An Overview of the Distributed Space Exploration Simulation (DSES) Project
This paper describes the Distributed Space Exploration Simulation (DSES) Project, a research and development collaboration between NASA centers which investigates technologies, and processes related to integrated, distributed simulation of complex space systems in support of NASA's Exploration Initiative. In particular, it describes the three major components of DSES: network infrastructure, software infrastructure and simulation development. With regard to network infrastructure, DSES is developing a Distributed Simulation Network for use by all NASA centers. With regard to software, DSES is developing software models, tools and procedures that streamline distributed simulation development and provide an interoperable infrastructure for agency-wide integrated simulation. Finally, with regard to simulation development, DSES is developing an integrated end-to-end simulation capability to support NASA development of new exploration spacecraft and missions. This paper presents the current status and plans for these three areas, including examples of specific simulations.
Distributed Simulation for Space Exploration
This viewgraph presentation reviews the use of simulation and modeling in preparation for the planned exploration initiatives. The Exploration Systems Mission Directorate (EMSD) Integrated Modeling and Simulation (IM&S) team strategy encompasses a wide spectrum of simulation and modeling policies and technologies. One prominent technology is distributed simulation. The DIstributed Simulation (DIS),a collaborative simulation project with international participation (US and Japan) is reviewed as an example of distributed simulation development. The Distributed Space Exploration Simulation (DSES) is another example of distributed simulation that is described
Generic Kalman Filter Software
The Generic Kalman Filter (GKF) software provides a standard basis for the development of application-specific Kalman-filter programs. Historically, Kalman filters have been implemented by customized programs that must be written, coded, and debugged anew for each unique application, then tested and tuned with simulated or actual measurement data. Total development times for typical Kalman-filter application programs have ranged from months to weeks. The GKF software can simplify the development process and reduce the development time by eliminating the need to re-create the fundamental implementation of the Kalman filter for each new application. The GKF software is written in the ANSI C programming language. It contains a generic Kalman-filter-development directory that, in turn, contains a code for a generic Kalman filter function; more specifically, it contains a generically designed and generically coded implementation of linear, linearized, and extended Kalman filtering algorithms, including algorithms for state- and covariance-update and -propagation functions. The mathematical theory that underlies the algorithms is well known and has been reported extensively in the open technical literature. Also contained in the directory are a header file that defines generic Kalman-filter data structures and prototype functions and template versions of application-specific subfunction and calling navigation/estimation routine code and headers. Once the user has provided a calling routine and the required application-specific subfunctions, the application-specific Kalman-filter software can be compiled and executed immediately. During execution, the generic Kalman-filter function is called from a higher-level navigation or estimation routine that preprocesses measurement data and post-processes output data. The generic Kalman-filter function uses the aforementioned data structures and five implementation- specific subfunctions, which have been developed by the user on the basis of the aforementioned templates. The GKF software can be used to develop many different types of unfactorized Kalman filters. A developer can choose to implement either a linearized or an extended Kalman filter algorithm, without having to modify the GKF software. Control dynamics can be taken into account or neglected in the filter-dynamics model. Filter programs developed by use of the GKF software can be made to propagate equations of motion for linear or nonlinear dynamical systems that are deterministic or stochastic. In addition, filter programs can be made to operate in user-selectable "covariance analysis" and "propagation-only" modes that are useful in design and development stages.
SimTool - An object based approach to simulation construction
The creation and maintenance of large complex simulations can be a difficult and error prone task. A number of interactive and automated tools have been developed to aid in simulation construction and maintenance. Many of these tools are based upon object oriented analysis and design concepts. One such tool, SimTool, is an object based integrated tool set for the development, maintenance, and operation of large, complex and long lived simulations. This paper discusses SimTool's object based approach to simulation design, construction and execution. It also discusses the services provided to various levels of SimTool users to assist them in a wide range of simulation tasks. Also, with the aid of an implemented and working simulation example, this paper discusses SimTool's key design and operational features. Finally, this paper presents a condensed discussion of SimTool's Entity-Relationship-Attribute (ERA) modeling approach.
Approximate optimal atmospheric guidance law for aeroassisted plane-change maneuvers
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An approximate atmospheric guidance law for aeroassisted plane change maneuvers
An approximate optimal guidance law for the aeroassisted plane change problem is presented which is based upon an expansion of the Hamilton-Jacobi-Bellman equation with respect to the small parameter of Breakwell et al. (1985). The present law maximizes the final velocity of the reentry vehicle while meeting terminal constraints on altitude, flight path angle, and heading angle. The integrable zeroth-order solution found when the small parameter is set to zero corresponds to a solution of the problem where the aerodynamic forces dominate the inertial forces. Higher order solutions in the expansion are obtained from the solution of linear partial differential equations requiring only quadrature integration.