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Modular Aero-Propulsion System Simulation

The Modular Aero-Propulsion System Simulation (MAPSS) is a graphical simulation environment designed for the development of advanced control algorithms and rapid testing of these algorithms on a generic computational model of a turbofan engine and its control system. MAPSS is a nonlinear, non-real- time simulation comprising a Component Level Model (CLM) module and a Controller-and-Actuator Dynamics (CAD) module. The CLM module simulates the dynamics of engine components at a sampling rate of 2,500 Hz. The controller submodule of the CAD module simulates a digital controller, which has a typical update rate of 50 Hz. The sampling rate for the actuators in the CAD module is the same as that of the CLM. MAPSS provides a graphical user interface that affords easy access to engine-operation, engine-health, and control parameters; is used to enter such input model parameters as power lever angle (PLA), Mach number, and altitude; and can be used to change controller and engine parameters. Output variables are selectable by the user. Output data as well as any changes to constants and other parameters can be saved and reloaded into the GUI later.

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Generic Environment for Simulating Launch Operations

GEM-FLO (A Generic Simulation Environment for Modeling Future Launch Operations) is a computer program that facilitates creation of discreteevent simulation models of ground processes in which reusable or expendable launch vehicles (RLVs) are prepared for flight. GEM-FLO includes a component, developed in Visual Basic, that generates a graphical user interface (GUI) and a component, developed in the Arena simulation language, that creates a generic discrete-event simulation model. Through the GUI, GEM-FLO elicits RLV design information from the user. The design information can include information on flight hardware elements, resources, and ground processes. GEMFLO translates the user’s responses into mathematical variables and expressions that populate the generic simulation model. The variables and expressions can represent processing times, resource capacities, status variables, and other process parameters needed to configure a simulation model that reflects the ground processing flow and requirements of a specific RLV. Upon execution of the model, GEM-FLO puts out data on many measures of performance, including the flight rate, turnaround time, and utilization of resources. This information can serve as the basis for determining whether design goals can be met, and for comparing characteristics of competing RLV designs.

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Infrastructure for Rapid Development of Java GUI Programs

The Java Application Shell (JAS) is a software framework that accelerates the development of Java graphical-userinterface (GUI) application programs by enabling the reuse of common, proven GUI elements, as distinguished from writing custom code for GUI elements. JAS is a software infrastructure upon which Java interactive application programs and graphical user interfaces (GUIs) for those programs can be built as sets of plug-ins. JAS provides an application- programming interface that is extensible by application-specific plugins that describe and encapsulate both specifications of a GUI and applicationspecific functionality tied to the specified GUI elements. The desired GUI elements are specified in Extensible Markup Language (XML) descriptions instead of in compiled code. JAS reads and interprets these descriptions, then creates and configures a corresponding GUI from a standard set of generic, reusable GUI elements. These elements are then attached (again, according to the XML descriptions) to applicationspecific compiled code and scripts. An application program constructed by use of JAS as its core can be extended by writing new plug-ins and replacing existing plug-ins. Thus, JAS solves many problems that Java programmers generally solve anew for each project, thereby reducing development and testing time.

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DCS-Neural-Network Program for Aircraft Control and Testing

A computer program implements a dynamic-cell-structure (DCS) artificial neural network that can perform such tasks as learning selected aerodynamic characteristics of an airplane from windtunnel test data and computing realtime stability and control derivatives of the airplane for use in feedback linearized control. A DCS neural network is one of several types of neural networks that can incorporate additional nodes in order to rapidly learn increasingly complex relationships between inputs and outputs. In the DCS neural network implemented by the present program, the insertion of nodes is based on accumulated error. A competitive Hebbian learning rule (a supervised-learning rule in which connection weights are adjusted to minimize differences between actual and desired outputs for training examples) is used. A Kohonen-style learning rule (derived from a relatively simple training algorithm, implements a Delaunay triangulation layout of neurons) is used to adjust node positions during training. Neighborhood topology determines which nodes are used to estimate new values. The network learns, starting with two nodes, and adds new nodes sequentially in locations chosen to maximize reductions in global error. At any given time during learning, the error becomes homogeneously distributed over all nodes.

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Computing Isentropic Flow Properties of Air/ R-134a Mixtures

MACHRK is a computer program that calculates isentropic flow properties of mixtures of air and refrigerant R-134a (tetrafluoroethane), which are used in transonic aerodynamic testing in a wind tunnel at Langley Research Center. Given the total temperature, total pressure, static pressure, and mole fraction of R-134a in a mixture, MACHRK calculates the Mach number and the following associated flow properties: dynamic pressure, velocity, density, static temperature, speed of sound, viscosity, ratio of specific heats, Reynolds number, and Prandtl number. Real-gas effects are taken into account by treating the gases comprising the mixture as both thermally and calorically imperfect. The Redlich-Kwong equation of state for mixtures and the constant-pressure ideal heat-capacity equation for the mixture are used in combination with the departure-function approach of thermo thermodynamics to obtain the equations for computing the flow properties. In addition to the aforementioned calculations for air/R-134a mixtures, a research version of MACHRK can perform the corresponding calculations for mixtures of air and R- 12 (dichlorodifluoromethane) and for air/SF6 mixtures. [R-12 was replaced by R- 134a because of environmental concerns. SF6 has been considered for use in increasing the Reynolds-number range.]

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Java Mission Evaluation Workstation System

The Java Mission Evaluation Workstation System (JMEWS) is a collection of applications designed to retrieve, display, and analyze both real-time and recorded telemetry data. This software is currently being used by both the Space Shuttle Program (SSP) and the International Space Station (ISS) program. JMEWS was written in the Java programming language to satisfy the requirement of platform independence. An object-oriented design was used to satisfy additional requirements and to make the software easily extendable. By virtue of its platform independence, JMEWS can be used on the UNIX workstations in the Mission Control Center (MCC) and on office computers. JMEWS includes an interactive editor that allows users to easily develop displays that meet their specific needs. The displays can be developed and modified while viewing data. By simply selecting a data source, the user can view real-time, recorded, or test data.

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Software for Automated Generation of Cartesian Meshes

Cart3D is a collection of computer programs for generating Cartesian meshes [for computational fluid dynamics (CFD) and other applications] in volumes bounded by solid objects. Aspects of Cart3D at earlier stages of development were reported in “Robust and Efficient Generation of Cartesian Meshes for CFD” (ARC-14275), NASA Tech Briefs, Vol. 23, No. 8 (August 1999), page 30. The geometric input to Cart3D comprises surface triangulations like those commonly generated by computer- aided-design programs. Complexly shaped objects can be represented as assemblies of simpler ones. Cart3D deletes all portions of such an assembled object that are not on the exterior surface. Intersections between components are preserved in the resulting triangulation. A tie-breaking routine unambiguously resolves geometric degeneracies. Then taking the intersected surface triangulation as input, the volume mesh is generated through division of cells of an initially coarse hexahedral grid. Cells are subdivided to refine the grid in regions of increased surface curvature and/or increased flow gradients. Cells that become split into multiple unconnected regions by thin pieces of surface are identified.

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