scholarly journals Model-based System Safety Assessment of Aircraft Power Plant

2014 ◽  
Vol 80 ◽  
pp. 85-92 ◽  
Author(s):  
Yan Li ◽  
Qi Gong ◽  
Duo Su
Keyword(s):  
Power Plant ◽  
Safety Assessment ◽  
System Safety ◽  
Model Based

scholarly journals Model-based safety assessment for conceptual aircraft systems design

2021 ◽  
Author(s):  
Simon Gradel ◽  
Benedikt Aigner ◽  
Eike Stumpf
Keyword(s):  
Conceptual Design ◽  
Safety Assessment ◽  
Aircraft Design ◽  
System Safety ◽  
Design Studies ◽  
System Architectures ◽  
Architecture Model ◽  
Model Based ◽  
Technology Modeling ◽  
Conceptual Aircraft Design

AbstractTraditional system technology modeling in conceptual aircraft design mainly relies on empirical knowledge and methods derived from conventional systems, for which valid system architecture designs are known. Since these systems have been proven valid especially from a safety perspective, detailed system safety analyses are usually not necessary. For unconventional systems and innovative technologies, on contrary, new architectures have to be designed and system safety has, therefore, to be taken into account. Therefore, the application of model-based safety assessment (MBSA) for designing system architectures in conceptual aircraft design studies is proposed. A MBSA approach based on a Simulink architecture model is presented which is tailored for use in conceptual design studies. It is applied to the cryocooling system of a hybrid-electric powertrain architecture from an already-published study. The original architecture as well as possible architecture alternatives are investigated. As a result, a safer architecture version with lower number of components can be proposed. The application example indicates that using MBSA in conceptual design benefits the latter by providing insights into safety properties of the system and by pointing out architecture safety weaknesses. This could result in safer, thus more realistic system architectures.

ADS-B: Probabilistic Safety Assessment

2017 ◽  
Vol 70 (4) ◽  
pp. 887-906 ◽  
Author(s):  
Busyairah Syd Ali ◽  
Washington Yotto Ochieng ◽  
Arnab Majumdar
Keyword(s):  
Safety Assessment ◽  
Failure Modes ◽  
Fault Tree Analysis ◽  
Performance Standards ◽  
System Safety ◽  
Probabilistic Safety Assessment ◽  
Assessment Approach ◽  
Primary Means ◽  
Importance Analysis ◽  
Probabilistic Safety

In the effort to quantify Automatic Dependent Surveillance Broadcast (ADS-B) system safety, the authors have identified potential ADS-B failure modes in Syd Ali et al. (2014). Based on the findings, six potential hazards of ADS-B are identified in this paper. The authors then applied the Probabilistic Safety Assessment approach which includes Fault Tree Analysis (FTA) and Importance Analysis methods to quantify the system safety. FTA is applied to measure ADS-B system availability for each identified hazard while Importance Analysis is conducted to identify the most significant failure modes that may lead to the occurrence of the hazards. In addition, risk significance and safety significance of each failure mode are also identified. The result shows that the availability for the ADS-B system as a sole surveillance means is low at 0·898 in comparison to the availability of ADS-B system as supplemental or as primary means of surveillance at 0·95 and 0·999 respectively. The latter availability values are obtained from Minimum Aviation System Performance Standards (MASPS) for Automatic Dependent Surveillance-Broadcast (DO-242A).

scholarly journals Identification of a Generator Fault by Model-Based Diagnostic Techniques

2004 ◽  
Vol 10 (4) ◽  
pp. 293-300 ◽  
Author(s):  
P. Pennacchi ◽  
A. Vania
Keyword(s):  
Experimental Data ◽  
Power Plant ◽  
Diagnostic Techniques ◽  
Rotating Machines ◽  
Identification Methods ◽  
Model Based

Model-based diagnostic techniques can be used successfully in the health analysis of rotormachinery. Unfortunately, a poor accuracy of the model of the fully assembled machine, as well as noise in the signals and errors in the evaluation of the experimental vibrations that are caused only by the impending fault, can affect the accuracy of the fault identifications. This can make it difficult to identify the type of actual fault as well as to evaluate with care its severity and position. This article shows some techniques that have been developed by the authors to measure the accuracy of the results obtained with model-based identification methods aimed to diagnose faults in rotating machines. In this article, the results obtained by means of the analysis of experimental data collected in a power plant are described. Finally, the capabilities of the developed methods are shown and discussed.

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