Safety‐oriented discrete event model for airport A‐SMGCS reliability assessment

A detailed analysis of State of the Art Technologies and Procedures into Airport Advanced-Surface Movement Guidance and Control Systems has been provided in this thesis, together with the review ofStatistical Monte Carlo Analysis, Reliability Assessment and Petri Nets theories. This practical and theoretical background has lead the author to the conclusion that there is a lack of linkage in between these fields. At the same of time the rapid increasing of Air Traffic all over the world, has brought in evidence the urgent need of practical instruments able to identify and quantify the risks connected with Aircraft operations on the ground, since the Airport has shown to be the actual ‘bottle neck’ of the entire Air Transport System. Therefore, the only winning approach to such a critical matter has to be multi-disciplinary, sewing together apparently different subjects, coming from the most disparate areas of interest and trying to fulfil the gap. The result of this thesis work has come to a start towards the end, when a Timed Coloured Petri Net (TCPN) model of a ‘sample’ Airport A-SMGCS has been developed, that is capable of taking into account different orders of questions arisen during these recent years and tries to give them some good answers. The A-SMGCS Airport model is, in the end, a parametric tool relying on Discrete Event System theory, able to perform a Reliability Analysis of the system itself, that: • uses a Monte Carlo Analysis applied to a Timed Coloured Petri Net, whose purpose is to evaluate the Safety Level of Surface Movements along an Airport • lets the user to analyse the impact of Procedures and Reliability Indexes of Systems such as Surface Movement Radars, Automatic Dependent Surveillance-Broadcast, Airport Lighting Systems, Microwave Sensors, and so on… onto the Safety Level of Airport Aircraft Transport System • not only is a valid instrument in the Design Phase, but it is useful also into the Certifying Activities an in monitoring the Safety Level of the above mentioned System with respect to changes to Technologies and different Procedures.This TCPN model has been verified against qualitative engineering expectations by using simulation experiments and occupancy time schedules generated a priori. Simulation times are good, and since the model has been written into Simulink/Stateflow programming language, it can be compiled to run real-time in C language (Real-time workshop and Stateflow Coder), thus relying on portable code, able to run virtually on any platform, giving even better performances in terms of execution time. One of the most interesting applications of this work is the estimate, for an Airport, of the kind of A-SMGCS level of implementation needed (Technical/Economical convenience evaluation). As a matter of fact, starting from the Traffic Volume and choosing the kind of Ground Equipment to be installed, one can make predictions about the Safety Level of the System: if the value is compliant with the TLS required by ICAO, the A-SMGCS level of Implementation is sufficiently adequate. Nevertheless, even if the Level of Safety has been satisfied, some delays due to reduced or simplified performances (even if Safety is compliant) of some of the equipment (e.g. with reference to False Alarm Rates) can lead to previously unexpected economical consequences, thus requiring more accurate systems to be installed, in order to meet also Airport economical constraints. Work in progress includes the analysis of the effect of weather conditions and re-sequencing of a given schedule. The effect of re-sequencing a given schedule is not yet enough realistic since the model does not apply inter arrival and departure separations. However, the model might show some effect on different sequences based on runway occupancy times. A further developed model containing wake turbulence separation conditions would be more sensitive for this case. Hence, further work will be directed towards: • The development of On-Line Re-Scheduling based on the available actual runway/taxiway configuration and weather conditions. • The Engineering Safety Assessment of some small Italian Airport A-SMGCSs (Model validation with real data). • The application of Stochastic Differential Equations systems in order to evaluate the collision risk on the ground inside the Place alone on the Petri Net, in the event of a Short Term Conflict Alert (STCA), by adopting Reich Collision Risk Model. • Optimal Air Traffic Control Algorithms Synthesis (Adaptive look-ahead Optimization), by Dynamically Timed Coloured Petri Nets, together with the implementation of Error-Recovery Strategies and Diagnosis Functions

Energy Storage System Control for Energy Management in Advanced Aeronautic Applications

In this paper an issue related to electric energy management on board an aircraft is considered. A battery pack is connected to a high-voltage bus through a controlled Battery Charge/Discharge Unit (BCDU) that makes the overall behaviour of the battery “intelligent.” Specifically, when the aeronautic generator feeding the high-voltage bus has enough energy the battery is kept under charge, while if more loads are connected to the bus, so that the overload capacity of the generator is exceeded, the battery “helps” the generator by releasing its stored energy. The core of the application is a robust, supervised control strategy for the BCDU that automatically reverts the flow of power in the battery, when needed. Robustness is guaranteed by a low-level high gain control strategy. Switching from full-charge mode (i.e., when the battery absorbs power from the generator) to generator mode (i.e., when the battery pumps energy on the high-voltage bus) is imposed by a high-level supervisor. Different from previous approaches, mathematical proofs of stability are given for the controlled system. A switching implementation using a finite-time convergent controller is also proposed. The effectiveness of the proposed strategy is shown by detailed simulations in Matlab/Stateflow/SimPowerSystem

Tree-Network Overrun Model Associated with Pilots’ Actions and Flight Operational Procedures

The runway excursions are defined as the exit of an aircraft from the surface of the runway. These excursions can take place at takeoff or at landing and consist of two types of events: veer off and overrun. This last one, which occurs when the aircraft exceeds the limits at the end of the runway, is the event of interest in the current study. This chapter aims to present an accident model with a new approach in aeronautical systems, based on the tasks of the pilots related to the operational procedures necessary for the approach and landing, in order to obtain the chain of events that lead to this type of accident. Thus, the tree-network overrun model (TNO model) was proposed, unlike most traditional models, which consider only the hardware failures or which do not satisfactorily explain the interrelationship between the factors influencing the operator. The proposed model is developed in a fault tree and transformed into a Bayesian network up to the level of the basic elements. The results showed the qualitative model of the main tasks performed by the pilots and their relation to the accident. It has also been suggested how to find and estimate the probability of factors that can impact on each of the tasks

Robust Control of Aeronautical Electrical Generators for Energy Management Applications

A new strategy for the control of aeronautical electrical generators via sliding manifold selection is proposed, with an associated innovative intelligent energy management strategy used for efficient power transfer between two sources providing energy to aeronautical loads, having different functionalities and priorities. Electric generators used for aeronautical application involve several machines, including a main generator and an exciter. Standard regulators (PI or PID-like) are normally used for the rectification of the generator voltage to be used to supply a high-voltage DC bus. The regulation is obtained by acting on a DC/DC converter that imposes the field voltage of the exciter. In this paper, the field voltage is fed to the generator windings by using a second-order sliding mode controller, resulting into a stable, robust (against disturbances) action and a fast convergence to the desired reference. By using this strategy, an energy management strategy is proposed that dynamically changes the voltage set point, in order to intelligently transfer power between two voltage busses. Detailed simulation results are provided in order to show the effectiveness of the proposed energy management strategy in different scenarios

Proceedings Work-In-Progress Session of the 13th Real-Time and Embedded Technology and Applications Symposium

The Work-In-Progress session of the 13th IEEE Real-Time and Embedded Technology and Applications Symposium (RTAS\u2707) presents papers describing contributions both to state of the art and state of the practice in the broad field of real-time and embedded systems. The 17 accepted papers were selected from 19 submissions. This proceedings is also available as Washington University in St. Louis Technical Report WUCSE-2007-17, at http://www.cse.seas.wustl.edu/Research/FileDownload.asp?733. Special thanks go to the General Chairs – Steve Goddard and Steve Liu and Program Chairs - Scott Brandt and Frank Mueller for their support and guidance

Fault Tree Analysis of Polymer Electrolyte Fuel Cells to predict degradation phenomenon

Hydrogen Fuel Cells are an electro-chemical, zero-emission energy conversion and power generation device. Their only products are heat and electrical energy, and water vapour. One of the major hurdles to the uptake of this technology is the reliability of the fuel cell system. This hurdle can be overcome through in depth reliability analysis including Failure Mode and Effect Analysis (FMEA) and Fault Tree analysis (FTA) amongst others. Research has found that the reliability research area regarding hydrogen fuel cells is still in its infancy, and needs development. This paper looks at the current state of the art in reliability analysis regarding Polymer Electrolyte Fuel Cells (PEMFC). A recent fault tree (FT) from the literature is qualitatively analysed to ascertain its practicality in relation to PEMFC degradation analysis. The fault tree was found to harbour certain aspects that could be improved upon. There was no FMEA undertaken to precede the FT which would have given a greater understanding of the possible failure modes in a PEMFC system and their relationships. The FT was found to be lacking dependant relationships which are apparent in a PEMFC system. The data from the literature was also analysed to check its relevance in today’s fast moving PEMFC research. Conclusions are given to the way forward for future reliability evaluation of PEMFCs

Impact of condition monitoring on the maintenance and economic viability of offshore wind turbines

This study explores how condition monitoring (CM) can help operate offshore wind turbines (OWTs) effectively and economically. In this paper, the Petri Net (PN) simulation models are developed to quantitatively assess the OWT availability and operation and maintenance (O&M) costs. By investigating the impact of two CM approaches (i.e. purpose-designed CM and Supervisory Control and Data Acquisition (SCADA)-based CM) and their combinations with various maintenance strategies, the paper addresses two fundamental questions about OWT CM that have plagued the offshore wind sector for many years. They are ‘is a wind farm SCADA system a viable alternative to purpose-designed condition monitoring system (CMS)’ and ‘what is the best way to integrate CMSs and maintenance strategies to maximise the financial benefit of OWTs’. The research suggests that although utilising both a wind farm SCADA system and a purpose-designed CMS can achieve the highest turbine availability, it is not the most cost-effective option in terms of maintenance expenses. Instead, combining purpose-designed CM with less frequent advanced service can achieve the desired availability at the lowest cost. Furthermore, the use of a purpose-designed CMS is essential for the economical operation of OWTs and cannot be replaced by the current wind farm SCADA system.</p

Enhanced Fault Tree analysis and modelling considerations of a Polymer Electrolyte Membrane Fuel Cell

With the recent increase in interest in environmental issues and climate change concerns, the scientific community have been tasked with developing low carbon technologies to mitigate against climate change. One of the most promising technologies is the hydrogen fuel cell, particularly when integrated into an automobile. Hydrogen Fuel Cells are an electro-chemical, zero-emission energy conversion and power generation device. Their only output products are heat, electrical energy, and water vapour. There are three main hurdles to the commercial uptake of this technology; Infrastructure, Cost and Reliability. An understanding of the reliability of fuel cells can be obtained through in-depth reliability analysis including techniques such as Failure Mode and Effect Analysis (FMEA) and Fault Tree analysis (FTA) amongst others. As hydrogen fuel cells are a relatively new technology this in-depth analysis is still in its infancy, and needs development. This research has extended the work on FTA of the Polymer Electrolyte Membrane Fuel Cell (PEMFC) systems. Detailed analysis has explored the inherent complexity of the PEMFC system where issues with using a basic FTA for a PEMFC, such as dependencies between failure modes, and disparities between failure mode operating principles, are discussed. The integration of the Markov technique, which can deal with dependencies, within the Fault tree approach is suggested as a mechanism to enhance the accuracy of the modelling of a PEMFC

Diagnosis of MEA degradation for health management of polymer electrolyte fuel cells

Diagnostics and health management are fundamental components in a strategy to improve durability and lifetime of polymer electrolyte fuel cells. Fuel cells require a range of operating conditions to be well managed for achieving performance or durability objectives. So far, water management issues and single parameter diagnostics for individual degradation modes have been the focus of research in the literature. However, there has been minimal research on the application of fuzzy inference systems for online, multiple parameter diagnosis of fuel cells. This research presents an advanced fuzzy inference system for diagnostics and health management of a membrane electrode assembly (MEA) for polymer electrolyte fuel cells. The fuzzy inference system facilitates simplified connections of the complex relationships between numerous operating conditions and subsequent degradation modes. The approach utilises the most important operating parameters for diagnosis of high priority degradation modes using multiple health sensors. The developed fuzzy inference system classifies the fuel cell input data into simple linguistic categories for example ‘cell voltage is very high’ or ‘stack temperature is low’ through a fuzzification process. Based on a set of antecedent-consequent (if-then) rules, an inference calculation is performed without necessity for complex mathematical models. This enables a fast diagnosis with fuel cell parameters classified on a scale of inclusion to the linguistic categories. The linguistic classification of a degradation mode is converted back into a numerical value through a defuzzification process. The output data can be used to inform the user on the fuel cell state of health. The investigation has focused on the diagnosis of MEA degradation as it has been identified as having critical impact on fuel cell performance and lifetime. A single cell with a 25cm2 active area was used for testing under numerous moderate to extreme operating conditions known to cause membrane and electro-catalyst degradation. A database of if-then rules was initially developed based on knowledge in the literature and refined with experimental testing. Results so far have supported validation of the fuzzy inference system membership functions and the rule base for diagnosing the consequential degradation modes based on fuel cell operating conditions. This diagnostic and health management approach facilitates proactive decision making for mitigation strategies to be employed according to performance or lifetime targets and can increase fuel cell availability and lifetime therefore improving the overall value of the system.</div

Airspace Integration of New Entrants and Safety Risk Management Models

In recent years, the demand for airspace access of Unmanned Aerial Systems (UAS) increased significantly and is continuously increasing for different altitude-types UAS. A similar evolution is expected from Commercial Space Operations (CSO) in the next years. These aviation/aerospace systems will need to be seamlessly integrated into the National Airspace System (NAS), at their operational altitude levels, and accounted for from all perspectives, including proactively addressing their safety hazards. This thesis captures the requirements for the new entrants’ integration, and then identifies and analyzes the safety risks added to the NAS operations by its new entrants, the future omnipresent UAS on different NAS levels, and the coming CSO age. Methodologies such as Functional Hazard Analysis, Subsystem and System Hazard Analysis, and Safety Risk Management are explored and integrated into the airspace new entrants’ framework and models. In addition, techniques such as state-machine modeling and simulation are used on an identified use case of UAS operations in crowded airspace