Development of an Intelligent Monitoring and Control System for a Heterogeneous Numerical Propulsion System Simulation

4. Current Status and Future Directions

4.1 - Current State
4.2 - Future Directions
Acknowledgments
References

This is an on-going research project. This section describes the current state of the implementation and then outlines some of our plans for expansion of the system.

4.1 Current State

The TESS-ADPAC system has been fully implemented. It has been tested with a subsonic engine model and compared with experimental data from the Energy Efficient Engine. The machine suite used for the tests consisted of a Silicon Graphics Iris 4D/440VGX at the University of Toledo for the TESS system. The ADPAC instances were executed on a variable number of nodes of the Lace cluster, a network of 32 IBM RS6000 workstations located at the NASA Lewis Research Center.

The monitoring tool was originally designed to monitor a single ADPAC instance. This was a result of the original zooming strategy which envisioned a single high-fidelity component simulation used in an iterative approach (see Section 2.1). The monitoring tool has been tested on a Sun Sparc 10 workstation located at the Lewis Research Center and monitoring an ADPAC run on a node of the Lace cluster. In this prototype, the expert system executes on the same platform as the monitoring tool, since the initial number of rules is small. The system is currently being extended to monitor all instances of ADPAC and allow the user to select all, or a subset, to observe. The expert system can be moved to a separate platform as soon as the complexity of the rules increases to the point where this will be necessary.

4.2 Future Directions

One obvious direction is to modify the source code of ADPAC to allow it to communicate directly with TESS and the monitoring and control system, rather than through its output files. A principal reason for not modifying the source initially is the desire to prove the feasibility of this approach and identify the specific changes desired. There is another positive feature to the approach of using the output files: It would be relatively straight-forward to substitute a different high-fidelity fan simulation and provide a similar level of monitoring through watching its output file. This technique allows for easy testing of different fan simulations without the initial need to involve the authors of the simulation. The technique also supports the inclusion of commercial CFD tools, where source is typically not available.

The ADPAC code is currently being re-written to take advantage of parallel machines and workstation clusters. Once this work is completed, the parallel-ADPAC will be tested with the TESS system.

Another zooming approach being studied is to use an intermediate fan simulation, specifically a two-dimensional, axi-symmetric simulation. This has the advantage of not requiring as much execution time as the three-dimensional ADPAC simulation when less accuracy is needed. In addition, it will be possible in some cases to use the solution from the medium-fidelity simulation to jump-start the three-dimensional solution, thus shortening the execution time of the high-fidelity simulation.

Fault detection and fault tolerance techniques are being studied for use with the multiple ADPAC runs. Currently, the system does not gracefully handle the failure of an ADPAC instance. In general, the desired single curve performance map can be created even when one or two ADPAC instances fail, allowing the simulation to proceed. This is an area where rules are needed for the expert system so the user will not have to constantly monitor a long simulation in case a fault occurs.

Acknowledgments

The NPSS project is managed by the Interdisciplinary Technology Office (ITO) at NASA Lewis Research Center (LeRC). This work was performed in part on computing resources at the Advanced Computational Concepts Laboratory (ACCL) and the Computer Services Division at LeRC. Thanks are due to G. Follen, C. Putt and C. Miller of LeRC. This work has been supported in part by the following grants: NSF grant ASC-9204021, NASA grants NGT-50966, NAG3-1560, and NCC-3-207.

References

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Engine Simulation: Intelligent Monitoring and Control

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