Thermal Simulation Tool

One outcome of intelligent control and autonomy research is useful, cutting-edge software tools that support the development, modeling, analysis, and testing of advanced/intelligent control designs and systems health management capabilities. Many of these software tools have been made available to the public through NASA’s software and GitHub websites.

The publicly available software tools highlighted here support control system design and analysis, systems health management, propulsion system modeling, unsteady combustion modeling, and propulsion component modeling. Systems Analysis is typically done with steady-state performance in mind. However, for complex systems such as aircraft engines, the capability to meet transient performance requirements over a wide operating envelope and a long operating life is critical.

Dynamic Systems Analysis (DSA) tools and techniques have been developed which can be used to evaluate competing configurations and technologies from the perspective of being able to meet transient performance, operational life and safety requirements.

The Tool for Turbine Engine Closed-loop Transient analysis (TTECTrA) was developed as an initial step for DSA of turbofan engines.

TTECTrA is an open-source software tool developed in the MATLAB/Simulink environment. The purpose of this tool is to provide the user a preliminary estimate of the transient performance of an aircraft engine without the need to design a full nonlinear controller. It is anticipated that more efficient engine designs will result by accounting for the dynamic performance capability early in the engine design stage. The TTECTrA generic closed-loop architecture. The Setpoint, PI controller, Accel Limiter, and Decel Limiter subsystems are designed by the TTECTrA controller, whereas the Actuator and Pre-Filter subsystems are user-defined.

and Zinnecker, A.M., “Tool for Turbine Engine Closed-Loop Transient Analysis (TTECTrA) Users’ Guide,” NASA/TM-2014-216663, June 2014. and Zinnecker, A.M., “Application of the Tool for Turbine Engine Closed-loop Transient Analysis (TTECTrA) for Dynamic Systems Analysis,” AIAA 2014-3975, AIAA Propulsion and Energy Forum, Cleveland, OH, June 28-30, 2014.

Propulsion Component and Other Modeling Tools

The TTECTrA tool can be downloaded directly from the NASA GitHub Repository.

  • The Extended Testability Analysis (ETA) Tool software was developed to extend the testability analysis capabilities of Qualtech Systems Inc.’s Testability Engineering And Maintenance System (TEAMS) Designer software.
  • TEAMS Designer is commercial-off-the-shelf software with the capability to qualitatively model and analyze the propagation of faults through a modeled system.
  • The ETA Tool extracts information from the TEAMS Designer output and the associated diagnostic model to provide detailed testability analysis reports that characterize the system’s diagnostic performance.

Information provided by these reports was shown to be a powerful tool for assessing compliance with system fault management requirements early in NASA’s Ares I and Artemis I design cycles. The ETA Tool software package includes a User Guide and all files required to execute the ETA Tool software with a TEAMS example application/model. The TEAMS Designer software is not included in the ETA Tool software package.

Unsteady Combustion Modeling Tools

First, a fault propagation model of the system is created with TEAMS Designer – requires use of Failure Mode and Effects Analysis (FMEA) and ETA Tool naming conventions. Second, TEAMS Designer is used to generate a dependency matrix that relates failure modes to sensor-based failure detection tests. Finally, the ETA Tool can be used with model information to analyze the dependency matrix and generate testability analysis reports. Detectability Report – Identifies failure modes that can be detected by each available failure detection test. Also identifies those failure modes that cannot be detected with any of the available failure detection tests.

Control System Design & Analysis

Allows users to identify and add tests/sensors required to detect critical failure modes early in the design process. Test Utilization Report – Identifies available failure detection tests that can be used to detect each failure mode. Also identifies failure mode detection tests that detect no failure modes. Allows users to identify and eliminate unnecessary tests/sensors. Failure Mode Isolation Report – Identifies each failure mode that can be isolated, i.e., detected solely with a unique set of failure detection tests.

For failure modes that cannot be isolated, identifies ambiguity groups; where an ambiguity group is composed of multiple failure modes that are each detected with the same unique set of tests. Allows user to verify compliance with requirements to isolate individual failure modes.

Propulsion System Modeling Tools

Additional tests/sensors could be identified early in the design process that could differentiate ambiguous failures. Component Isolation Report – Identifies each failure mode that can be isolated to a specific user-defined component.

  • For failure modes that cannot be isolated to a specific component, identifies component-associated ambiguity groups.
  • Similar to failure mode isolation, with this report the user can verify component failure isolation requirements and identify tests/sensor to differentiate ambiguities.
  • Effect Mapping Report – Identifies each failure mode that can be mapped to user-defined system effects. Supports an assessment of the effect of failures on the system, e.g., vehicle-level loss of mission analysis and probability risk assessment.
  • Sensor Sensitivity Report – Assesses change in diagnostic performance resulting from the removal of individual sensors or groups of sensors. The analysis can facilitate various design studies to determine the importance of specific tests/sensors, as well as diagnostic strategies to overcome sensor signal loss.

and Fulton, C.E., “Software Users Manual (SUM) Extended Testability Analysis (ETA) Tool, NASA/CR-2011-217240, November 2011. and Maul, W., “Verification of Functional Fault Models and the Use of Resource Efficient Verification Tools,” AIAA 2015-1796, AIAA Science and Technology Forum, Kissimmee, FL, January 5-9, 2015.

The ETA Tool software is available from the NASA Glenn Software Catalog. ProDiMES provides a standard benchmarking problem and evaluation metrics to enable a blind test case comparison of candidate aircraft engine gas path diagnostic methods.

Systems Health Management Tools

Many of the propulsion gas path diagnostic method solutions published in the open literature are applied to different platforms, with different levels of complexity, addressing different problems, and using different metrics for evaluating performance. As such, it is difficult to perform a one-to-one comparison of candidate approaches. Furthermore, these inconsistencies create barriers to the effective development of new algorithms and the exchange of results.

To help address these issues, the Propulsion Diagnostic Method Evaluation Strategy (ProDiMES) software tool has been specifically designed with the intent to be made publicly available. In this form it can serve as a reference, or theme problem, to aid in propulsion gas path diagnostic technology development and evaluation. The overall goal is to provide a tool that will serve as an industry standard that will facilitate the development and evaluation of significant EHM (Engine Health Management) capabilities.

Simon, D.L., “Propulsion Diagnostic Method Evaluation Strategy (ProDiMES) User’s Guide,” NASA/TM-2010-215840, January 2010. Simon, D.L., Borguet, S., Leonard, O., and Zhang, X., “Aircraft Engine Gas Path Diagnostic Methods, Public Benchmarking Results,” GTP13-1299, Journal of Engineering for Gas Turbines and Power. Apr 2014, 136(4): 041201. ProDIMES may be requested from NASA Software. The Systematic Sensor Selection Strategy (S4) is a methodical approach for identifying a suite of sensors that optimally meets engineering requirements for a given application.

The Tool for Turbine Engine Closed-loop Transient Analysis (TTECTrA)

S4 was developed to address the limitations of traditional aerospace sensor selection approaches that struggle to provide optimally effective sensor suite solutions for complex, interdependent system and subsystem requirements with sometimes difficult-to-identify and conflicting constraints. In aerospace vehicle design, the proper selection of sensors is necessary to ensure that operational, maintenance performance, and more recently, system health assessment requirements are met.

Traditional approaches to measurement and sensor selection for aerospace propulsion applications are generally heuristic and are typically directed toward measuring performance characteristics rather than health diagnostics. A typical sensor selection process begins with component teams submitting lists of desired measurements.

Compressible Flow Toolbox

These measurements are used to support engine development, model verification and/or detection of structural limit violations. As the system design matures, the component teams supply more detailed specifications such as measurement ranges, response requirements, and so forth. This information along with reliability requirements is used to determine the type and number of sensors needed at each system location.

  • The compiled list is then separated into categories associated with measurement use, such as ground test, flight, etc. Measurements are assigned a priority, with the highest priority given to measurements required for system control.
  • The list is often condensed as the design matures due to factors such as accessibility, cable routing, or reduced need. A maximum number of sensors is determined based on storage and transmission capability, cost, and other considerations which may include arbitrary limits.
  • The component teams and chief engineer then negotiate until the final suite is selected. Consequently, sensor selection approaches such as this draw heavily on domain expertise and do not utilize a consistent quantitative method to assess the implications of measurement choices on diagnostic capability.

The Systematic Sensor Selection Strategy (diagramed above) is best described as a general architecture structured to accommodate application-specific components and requirements. Each element is intended to be customized for the target system application. The methodology is flexible and is meant to be tailored to the specific application needs. Originally developed by NASA to support liquid propellant rocket engine health management, the S4 architecture offers the flexibility and versatility needed to support a broad range of applications, such as air-breathing engines, power systems, life support systems, ground support equipment, and general integrated vehicle health monitoring.

Sowers, T.S., “Systematic Sensor Selection Strategy (S4) User Guide,” NASA/TM-2012-215242, February 2012. Sowers, T.S., Kopasakis, G., and Simon, D.L., “Application of the Systematic Sensor Selection Strategy for Turbofan Engine Diagnostics,” NASA/TM-2008-215200, May 2008.

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