User's Guide for the Commercial Modular Aero-Propulsion System Simulation (C-MAPSS)

Home
/
Papers
/
User's Guide for the Commercial Modular Aero-Propulsion System Simulation (C-MAPSS)

User's Guide for the Commercial Modular Aero-Propulsion System Simulation (C-MAPSS)

Dean K. Frederick, Jonathan A. DeCastro¹, Jonathan S. Litt²•Institutions (2)

ASRC Aerospace Corporation¹, United States Department of the Army²

01 Oct 2007-

TL;DR: This report is a Users Guide for the NASA-developed Commercial Modular Aero-Propulsion System Simulation (C-MAPSS) software, which is a transient simulation of a large commercial turbofan engine with a realistic engine control system.

read less

Abstract: This report is a Users Guide for the NASA-developed Commercial Modular Aero-Propulsion System Simulation (C-MAPSS) software, which is a transient simulation of a large commercial turbofan engine (up to 90,000-lb thrust) with a realistic engine control system. The software supports easy access to health, control, and engine parameters through a graphical user interface (GUI). C-MAPSS provides the user with a graphical turbofan engine simulation environment in which advanced algorithms can be implemented and tested. C-MAPSS can run user-specified transient simulations, and it can generate state-space linear models of the nonlinear engine model at an operating point. The code has a number of GUI screens that allow point-and-click operation, and have editable fields for user-specified input. The software includes an atmospheric model which allows simulation of engine operation at altitudes from sea level to 40,000 ft, Mach numbers from 0 to 0.90, and ambient temperatures from -60 to 103 F. The package also includes a power-management system that allows the engine to be operated over a wide range of thrust levels throughout the full range of flight conditions.

...read moreread less

Content maybe subject to copyright Report

Citations

PDF

Open Access

More filters

Proceedings Article•DOI•

Damage propagation modeling for aircraft engine run-to-failure simulation

[...]

Abhinav Saxena¹, Kai Goebel², D. Simon³, Neil Holger White Eklund⁴•Institutions (4)

Research Institute for Advanced Computer Science¹, Ames Research Center², Glenn Research Center³, General Electric⁴

12 Dec 2008

TL;DR: In this article, the authors describe how damage propagation can be modeled within the modules of aircraft gas turbine engines and generate response surfaces of all sensors via a thermo-dynamical simulation model.

...read moreread less

Abstract: This paper describes how damage propagation can be modeled within the modules of aircraft gas turbine engines. To that end, response surfaces of all sensors are generated via a thermo-dynamical simulation model for the engine as a function of variations of flow and efficiency of the modules of interest. An exponential rate of change for flow and efficiency loss was imposed for each data set, starting at a randomly chosen initial deterioration set point. The rate of change of the flow and efficiency denotes an otherwise unspecified fault with increasingly worsening effect. The rates of change of the faults were constrained to an upper threshold but were otherwise chosen randomly. Damage propagation was allowed to continue until a failure criterion was reached. A health index was defined as the minimum of several superimposed operational margins at any given time instant and the failure criterion is reached when health index reaches zero. Output of the model was the time series (cycles) of sensed measurements typically available from aircraft gas turbine engines. The data generated were used as challenge data for the prognostics and health management (PHM) data competition at PHMpsila08.

...read moreread less

1,036 citations

Cites methods from "User's Guide for the Commercial Mod..."

...To ensure that the output of the model was producing correct results, we first generated response surfaces for sensed outputs and operability margins from C-MAPSS as a function of flow and efficiency for specific modules....
[...]
...Simplified diagram of engine simulated in C-MAPSS [11] ....
[...]
...This and the observation of similar degradation trends in practice [10] motivated our use of an exponential term while modeling changes of health parameters in C-MAPSS....
[...]
...To that end, a reasonably large number of trajectories were created from C-MAPSS that had the following properties: 1) Simulation of degradation in HPC module under 6 different combinations of Altitude, TRA, and Mach number operational conditions....
[...]
...The software is coded in the MATLAB ® and Simulink ® environment, and includes a number of editable input parameters that allow the user to enter specific values of his/her own choice regarding operational profile, closed-loop controllers, environmental conditions, etc. C-MAPSS simulates an engine model of the 90,000 lb thrust class and the package includes an atmospheric model capable of simulating operations at (i) altitudes ranging from sea level to 40,000 ft, (ii) Mach numbers from 0 to 0.90, and (iii) sea-level temperatures from –60 to 103 °F....
[...]

Journal Article•DOI•

Direct Remaining Useful Life Estimation Based on Support Vector Regression

[...]

Racha Khelif, Brigitte Chebel-Morello, Simon Malinowski¹, Emna Laajili, Farhat Fnaiech², Noureddine Zerhouni - Show less +2 more•Institutions (2)

University of Rennes¹, Tunis University²

01 Mar 2017-IEEE Transactions on Industrial Electronics

TL;DR: Experimental results show that the performance of the proposed method is competitive with other existing approaches and has a positive impact on the accuracy of the prediction while reducing the computational time compared to existing indirect RUL prediction methods.

...read moreread less

Abstract: Prognostics is a major activity in the field of prognostics and health management It aims at increasing the reliability and safety of systems while reducing the maintenance cost by providing an estimate of the current health status and remaining useful life (RUL) Classical RUL estimation techniques are usually composed of different steps: estimations of a health indicator, degradation states, a failure threshold, and finally the RUL In this work, a procedure that is able to estimate the RUL of equipment directly from sensor values without the need for estimating degradation states or a failure threshold is developed A direct relation between sensor values or health indicators is modeled using a support vector regression Using this procedure, the RUL can be estimated at any time instant of the degradation process In addition, an offline wrapper variable selection is applied before training the prediction model This step has a positive impact on the accuracy of the prediction while reducing the computational time compared to existing indirect RUL prediction methods To assess the performance of the proposed approach, the Turbofan dataset, widely considered in the literature, is used Experimental results show that the performance of the proposed method is competitive with other existing approaches

...read moreread less

281 citations

Cites background or methods from "User's Guide for the Commercial Mod..."

...The dataset is composed of multiple multivariate time series signals generated by a simulation model built on the Commercial Modular Aero-Propulsion System Simulation (C-MAPSS) [40]....
[...]
...signals generated by a simulation model built on the Commercial Modular Aero-Propulsion System Simulation (C-MAPSS) [40]....
[...]
...(b) Layout showing various modules and their connections as modeled in the simulation [40]....
[...]
...The C-MAPSS dataset has proven to be well adapted for the development of data-driven prognostics....
[...]
...[40] D. K. Frederick, J. A. DeCastro, and J. S. Litt, “Users guide for the commercial modular aero-propulsion system simulation (C-MAPSS),” NASA, Tech....
[...]

Journal Article•DOI•

A Data-Level Fusion Model for Developing Composite Health Indices for Degradation Modeling and Prognostic Analysis

[...]

Kaibo Liu¹, Nagi Gebraeel¹, Jianjun Shi¹•Institutions (1)

Georgia Institute of Technology¹

11 Apr 2013-IEEE Transactions on Automation Science and Engineering

TL;DR: This methodology includes data selection, data processing, and data fusion steps that lead to an improved degradation-based prognostic model that provides a much better characterization of the condition of a system compared to relying solely on data from an individual sensor.

...read moreread less

Abstract: Prognostics involves the effective utilization of condition or performance-based sensor signals to accurately estimate the remaining lifetime of partially degraded systems and components. The rapid development of sensor technology, has led to the use of multiple sensors to monitor the condition of an engineering system. It is therefore important to develop methodologies capable of integrating data from multiple sensors with the goal of improving the accuracy of predicting remaining lifetime. Although numerous efforts have focused on developing feature-level and decision-level fusion methodologies for prognostics, little research has targeted the development of “data-level” fusion models. In this paper, we present a methodology for constructing a composite health index for characterizing the performance of a system through the fusion of multiple degradation-based sensor data. This methodology includes data selection, data processing, and data fusion steps that lead to an improved degradation-based prognostic model. Our goal is that the composite health index provides a much better characterization of the condition of a system compared to relying solely on data from an individual sensor. Our methodology was evaluated through a case study involving a degradation dataset of an aircraft gas turbine engine that was generated by the Commercial Modular Aero-Propulsion System Simulation (C-MAPSS).

...read moreread less

245 citations

Cites methods from "User's Guide for the Commercial Mod..."

...Simplified engine diagram simulated in C-MAPSS [18]....
[...]
...A layout of modules and connections in the simulation [18]....
[...]
...The methodology was tested and validated using the degradation sensor data of aircraft gas turbine engine that were gener- ated by C-MAPSS [16]....
[...]
...The C-MAPSS simulation model is embedded in a MATLAB Simulink platform....
[...]
...2 provides a schematic diagram of a commercial aircraft gas turbine engine that was simulated using C-MAPSS....
[...]

Journal Article•DOI•

Hybrid PSO–SVM-based method for forecasting of the remaining useful life for aircraft engines and evaluation of its reliability

[...]

P.J. García Nieto¹, Esperanza García-Gonzalo¹, F. Sánchez Lasheras¹, F. J. de Cos Juez¹•Institutions (1)

University of Oviedo¹

01 Jun 2015-Reliability Engineering & System Safety

TL;DR: Remaining useful life values have been predicted here by using the hybrid PSO–SVM-based model from the remaining measured parameters (input variables) for aircraft engines with success.

...read moreread less

223 citations

Journal Article•DOI•

Data-driven remaining useful life prediction via multiple sensor signals and deep long short-term memory neural network.

[...]

Jun Wu¹, Kui Hu¹, Yiwei Cheng¹, Haiping Zhu¹, Xinyu Shao¹, Yuanhang Wang - Show less +2 more•Institutions (1)

Huazhong University of Science and Technology¹

01 Feb 2020-Isa Transactions

TL;DR: The experimental results demonstrate that the DLSTM model has a competitive performance in comparison with state-of-the-arts reported in literatures and other neural network models.

...read moreread less

Abstract: Remaining useful life (RUL) prediction is very important for improving the availability of a system and reducing its life cycle cost. This paper proposes a deep long short-term memory (DLSTM) network-based RUL prediction method using multiple sensor time series signals. The DLSTM model fuses multi-sensor monitoring signals for accurate RUL prediction, which is able to discover the hidden long-term dependencies among sensor time series signals through deep learning structure. By grid search strategy, the network structure and parameters of the DLSTM are efficiently tuned using an adaptive moment estimation algorithm so as to realize an accurate and robust prediction. Two various turbofan engine datasets are adopted to verify the performance of the DLSTM model. The experimental results demonstrate that the DLSTM model has a competitive performance in comparison with state-of-the-arts reported in literatures and other neural network models.

...read moreread less

183 citations

1
2
3
4
…
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41

Collapse

References

PDF

Open Access

More filters

Book•

Multivariable Feedback Design

[...]

Jan M. Maciejowski

01 Nov 1989

TL;DR: In this article, a comprehensive and unified view of modern multivariate feedback theory and design is presented, where balancing techniques with theory, the objective throughout is to enable the feedback engineer to design real systems.

...read moreread less

Abstract: Provides a comprehensive and unified view of modern multivariate feedback theory and design. Balancing techniques with theory, the objective throughout is to enable the feedback engineer to design real systems.

...read moreread less

1,576 citations

Book•

Multivariable Feedback Design

[...]

Maciejowsk

01 Nov 1990

TL;DR: This is the first text to give a comprehensive and unified view of modern multivariable feedback theory and design the feedback engineer to design real systems.

...read moreread less

Abstract: From the Publisher: This is the first text to give a comprehensive and unified view of modern multivariable feedback theory and design the feedback engineer to design real systems.

...read moreread less

1,464 citations

Proceedings Article•DOI•

A Modular Aero-Propulsion System Simulation of a Large Commercial Aircraft Engine

[...]

Jonathan A. DeCastro¹, Jonathan S. Litt², Dean K. Frederick•Institutions (2)

University of Rochester¹, Glenn Research Center²

01 Sep 2008

TL;DR: In this article, a simulation of a commercial engine has been developed in a graphical environment to meet the increasing need across the controls and health management community for a common research and development platform.

...read moreread less

Abstract: A simulation of a commercial engine has been developed in a graphical environment to meet the increasing need across the controls and health management community for a common research and development platform. This paper describes the Commercial Modular Aero Propulsion System Simulation (C-MAPSS), which is representative of a 90,000-lb thrust class two spool, high bypass ratio commercial turbofan engine. A control law resembling the state-of-the-art on board modern aircraft engines is included, consisting of a fan-speed control loop supplemented by relevant engine limit protection regulator loops. The objective of this paper is to provide a top-down overview of the complete engine simulation package.

...read moreread less

86 citations