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All sourcesNASA NTRSDOE OSTI
NASA NTRS1993

Estimation of Kalman filter gain from output residuals

This paper presents a procedure to estimate the Kalman filter gain from input-output measurement data with a given system model. The system model can be a finite element model or an experimental model from any identification method. The procedure consists of three basic steps. First, the stochastic portion related to the residuals of the response is computed. Second, the coefficients of a linear difference model for the stochastic portion are estimated by a least-squares solution that minimizes the filter residual. Third, the Kalman filter gain is computed from these model coefficients. Experimental results are presented to illustrate the usefulness of the developed procedure.

Juang, Jer-Nan↗
NASA NTRS2017

Modeling to Mars: a NASA Model Based Systems Engineering Pathfinder Effort

The NASA Engineering Safety Center (NESC) Systems Engineering (SE) Technical Discipline Team (TDT) initiated the Model Based Systems Engineering (MBSE) Pathfinder effort in FY16. The goals and objectives of the MBSE Pathfinder include developing and advancing MBSE capability across NASA, applying MBSE to real NASA issues, and capturing issues and opportunities surrounding MBSE. The Pathfinder effort consisted of four teams, with each team addressing a particular focus area. This paper focuses on Pathfinder team 1 with the focus area of architectures and mission campaigns. These efforts covered the timeframe of February 2016 through September 2016. The team was comprised of eight team members from seven NASA Centers (Glenn Research Center, Langley Research Center, Ames Research Center, Goddard Space Flight Center IV&V Facility, Johnson Space Center, Marshall Space Flight Center, and Stennis Space Center). Collectively, the team had varying levels of knowledge, skills and expertise in systems engineering and MBSE. The team applied their existing and newly acquired system modeling knowledge and expertise to develop modeling products for a campaign (Program) of crew and cargo missions (Projects) to establish a human presence on Mars utilizing In-Situ Resource Utilization (ISRU). Pathfinder team 1 developed a subset of modeling products that are required for a Program System Requirement Review (SRR)/System Design Review (SDR) and Project Mission Concept Review (MCR)/SRR as defined in NASA Procedural Requirements. Additionally, Team 1 was able to perform and demonstrate some trades and constraint analyses. At the end of these efforts, over twenty lessons learned and recommended next steps have been identified.

Phojanamongkolkij, Nipa↗
NASA NTRS2016

Application of Model-Based Systems Engineering for the Development of the Asteroid Redirect Robotic Mission

Model-Based Systems Engineering (MBSE) can augment existing Systems Engineering (SE) processes to more efficiently deliver enhanced products over the project life cycle. Using a multi-user accessible System Model, MBSE has been successfully deployed for the conceptual and preliminary design development of the Asteroid Redirect Robotic Mission (ARRM). The paper provides an overview and examples of the targeted MBSE deployment for development of the mission operational concept, system description, and functional requirements. The paper also includes description of the challenges and lessons learned.

Sindiy, Oleg V.↗
NASA NTRS1995

The Planetary Data System Web Catalog Interface--Another Use of the Planetary Data System Data Model

The Planetary Data System Data Model consists of a set of standardized descriptions of entities within the Planetary Science Community. These can be real entities in the space exploration domain such as spacecraft, instruments, and targets; conceptual entities such as data sets, archive volumes, and data dictionaries; or the archive data products such as individual images, spectrum, series, and qubes.

interface science metadata↗
NASA NTRS1982

Model reference adaptive control for linear time varying and nonlinear systems

Model reference adaptive control is applied to linear time varying systems and to nonlinear systems amenable to virtual linearization. Asymptotic stability is guaranteed even if the perfect model following conditions do not hold, provided that some sufficient conditions are satisfied. Simulations show the scheme to be capable of effectively controlling certain nonlinear systems.

Abida, L.↗
NASA NTRS1992

A fundamental theorem for the model reduction of nonlinear systems

A simple, but fundamental, theorem is given on the extent to which a nonlinear system model can have its order reduced. Essentially, the result is that the order, or the dimension of the state space representation, cannot be reduced to, or below, the dimension of the system's attractor. Several examples are given to illustrate this point. The result is especially applicable to higher order systems such as the infinite dimensional systems arising from the modeling of distributed parameter systems.

Mossayebi, Faramarz↗
NASA NTRS2017

Using A Model-Based Systems Engineering Approach For Exploration Medical System Development

NASA's Human Research Program's Exploration Medical Capabilities (ExMC) element is defining the medical system needs for exploration class missions. ExMC's Systems Engineering (SE) team will play a critical role in successful design and implementation of the medical system into exploration vehicles. The team's mission is to "Define, develop, validate, and manage the technical system design needed to implement exploration medical capabilities for Mars and test the design in a progression of proving grounds." Development of the medical system is being conducted in parallel with exploration mission architecture and vehicle design development. Successful implementation of the medical system in this environment will require a robust systems engineering approach to enable technical communication across communities to create a common mental model of the emergent engineering and medical systems. Model-Based Systems Engineering (MBSE) improves shared understanding of system needs and constraints between stakeholders and offers a common language for analysis. The ExMC SE team is using MBSE techniques to define operational needs, decompose requirements and architecture, and identify medical capabilities needed to support human exploration. Systems Modeling Language (SysML) is the specific language the SE team is utilizing, within an MBSE approach, to model the medical system functional needs, requirements, and architecture. Modeling methods are being developed through the practice of MBSE within the team, and tools are being selected to support meta-data exchange as integration points to other system models are identified. Use of MBSE is supporting the development of relationships across disciplines and NASA Centers to build trust and enable teamwork, enhance visibility of team goals, foster a culture of unbiased learning and serving, and be responsive to customer needs. The MBSE approach to medical system design offers a paradigm shift toward greater integration between vehicle and the medical system and directly supports the transition of Earth-reliant ISS operations to the Earth-independent operations envisioned for Mars. Here, we describe the methods and approach to building this integrated model.

Hanson, A.↗
NASA NTRS1977

Models and techniques for evaluating the effectiveness of aircraft computing systems

Models, measures and techniques were developed for evaluating the effectiveness of aircraft computing systems. The concept of effectiveness involves aspects of system performance, reliability and worth. Specifically done was a detailed development of model hierarchy at mission, functional task, and computational task levels. An appropriate class of stochastic models was investigated which served as bottom level models in the hierarchial scheme. A unified measure of effectiveness called 'performability' was defined and formulated.

Meyer, J. F.↗
NASA NTRS1974

TERSSE: Definition of the Total Earth Resources System for the Shuttle Era. Volume 7: User Models: A System Assessment

User models defined as any explicit process or procedure used to transform information extracted from remotely sensed data into a form useful as a resource management information input are discussed. The role of the user models as information, technological, and operations interfaces between the TERSSE and the resource managers is emphasized. It is recommended that guidelines and management strategies be developed for a systems approach to user model development.

Source record↗
NASA NTRSDate not supplied

System Safety Analysis of Complex NASA Systems with Model Based Engineering

The emergence of model-based engineering is transforming design and analysis methodologies [5]. A recognized benefit of model-based engineering is the existence of a “single source of truth” about the system that becomes the authoritative source of data and information for designers, analysts, and developers. This promotes consistency and efficiency as the design emerges and can be used to further optimize the design. Integrating System Safety Engineers to the “single source of truth” will ensure that the outputs of their assessments and analyses are relevant to the design as it evolves. Use of an integrated system model enables near immediate evaluation of a design change as well as development of operational processes for risk assessment and communication. Such models can enable efficient and timely analysis of system hazards (e.g., hazard fault tree analysis and procedure simulations) and produce complete, accurate, and more consistent products (e.g., hazard reports and safety requirement evaluations). Therefore, an agency-sponsored team at Goddard Space Flight Center (GSFC) recently completed a System Safety Study of modeling and testing capabilities as part of a Model-Based Safety and Mission Assurance Initiative (MBSMAI). Using an existing model developed for reliability analyses [1], GSFC modeling and system safety experts performed system safety analysis/modeling and produced safety products. The team evaluated model-based feasibility to support System Safety Engineering, developed safety analysis modeling processes, and identified tool capability advancement/development needs. These study results indicate model-based engineering is valid and useable for System

Model Based Engineering↗
NASA NTRS2006

System Architecture Modeling for Technology Portfolio Management using ATLAS

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

Thompson, Robert W.↗
NASA NTRS1987

A digital video model deformation system

The use of solid-state array cameras and a PC-controlled image acquisition system to measure model deformation in a wind tunnel is discussed. This digital system improves an earlier video model deformation system that used high-resolution tube cameras and required the manual measurement of targets on video hardcopy images. The new system eliminates both the vibration-induced distortion associated with tube cameras and the manual readup of video images necessary in the earlier version. Camera calibration and data reduction procedures necessary to convert pixel image plane data from two cameras into wing deflections are presented. Laboratory tests to establish the uncertainty of the system with the geometry to be used are described.

Burner, A. W.↗
NASA NTRS2009

Evaluating Effectiveness of Modeling Motion System Feedback in the Enhanced Hess Structural Model of the Human Operator

In order to use the Hess Structural Model to predict the need for certain cueing systems, George and Cardullo significantly expanded it by adding motion feedback to the model and incorporating models of the motion system dynamics, motion cueing algorithm and a vestibular system. This paper proposes a methodology to evaluate effectiveness of these innovations by performing a comparison analysis of the model performance with and without the expanded motion feedback. The proposed methodology is composed of two stages. The first stage involves fine-tuning parameters of the original Hess structural model in order to match the actual control behavior recorded during the experiments at NASA Visual Motion Simulator (VMS) facility. The parameter tuning procedure utilizes a new automated parameter identification technique, which was developed at the Man-Machine Systems Lab at SUNY Binghamton. In the second stage of the proposed methodology, an expanded motion feedback is added to the structural model. The resulting performance of the model is then compared to that of the original one. As proposed by Hess, metrics to evaluate the performance of the models include comparison against the crossover models standards imposed on the crossover frequency and phase margin of the overall man-machine system. Preliminary results indicate the advantage of having the model of the motion system and motion cueing incorporated into the model of the human operator. It is also demonstrated that the crossover frequency and the phase margin of the expanded model are well within the limits imposed by the crossover model.

Zaychik, Kirill↗
NASA NTRS1993

Modelling the Shuttle Remote Manipulator System: Another flexible model

High fidelity elastic system modeling algorithms are discussed. The particular system studied is the Space Shuttle Remote Manipulator System (RMS) undergoing full articulated motion. The model incorporates flexibility via a methodology the author has been developing. The technique is based in variational principles, so rigorous boundary condition generation and weak formulations for the associated partial differential equations are realized, yet the analyst need not integrate by parts. The methodology is formulated using vector-dyad notation with minimal use of tensor notation, therefore the technique is believed to be affable to practicing engineers. The objectives of this work are as follows: (1) determine the efficacy of the modeling method; and (2) determine if the method affords an analyst advantages in the overall modeling and simulation task. Generated out of necessity were Mathematica algorithms that quasi-automate the modeling procedure and simulation development. The project was divided into sections as follows: (1) model development of a simplified manipulator; (2) model development of the full-freedom RMS including a flexible movable base on a six degree of freedom orbiter (a rigid-body is attached to the manipulator end-effector); (3) simulation development for item 2; and (4) comparison to the currently used model of the flexible RMS in the Structures and Mechanics Division of NASA JSC. At the time of the writing of this report, items 3 and 4 above were not complete.

Barhorst, Alan A.↗
NASA NTRS1973

On optimal modeling of systems.

A procedure for modeling a linear system by an optimal finite-dimensional approximation is developed on the basis of Sard's (1967) generalized spline. Error bounds are given, and the application of the procedure is illustrated by two presented examples. The procedure may be employed, not only in the modeling of conventional lumped-parameter and distributed-parameter continuous dynamical systems, but also in mathematical operations such as those involved in pattern recognition and picture enhancement problems.

De Figueiredo, R. J. P.↗
NASA NTRS2017

Model-Based Systems Engineering Pathfinder: Informing the Next Steps

In 2016, the NASA Engineering and Safety Center established a model-based systems engineering (MBSE) Pathfinder. The primary motivations for establishing the MBSE Pathfinder were to advance the Agency's applications of MBSE and capture lessons-learned to inform the next steps. The MBSE Pathfinder had four teams working in parallel for eight months on different topics of interest to NASA. The teams were encouraged to learn, and use creativity and innovation in their system modeling. The results were captured via reports, webinars, and a knowledge capture meeting. The approach taken for the MBSE Pathfinder was very successful in providing a number of lessons-learned for NASA and for other organizations considering MBSE or pathfinder efforts, and in building a very strong and collaborative user community.

Weiland, Karen J.↗