Complex Aircraft Systems Research Articles

Integration of the Functional Hazard Assessment Within a Model-Based Systems Engineering Framework

A major challenge in developing novel aircraft concepts is demonstrating the safety of increasingly complex and multifunctional aircraft systems. Aircraft manufacturers are adopting model-based systems engineering approaches to develop these new aircraft. The safety assessment process follows suit with model-based safety assessment. However, system and safety engineers still transfer information that is mainly document-based during the system architecting process. This paper aims to improve this process. First, a framework for developing system architecture specification models is introduced using the Architecture Analysis and Design Integrated Approach (ARCADIA)/Capella methodology and tool, illustrated with an aircraft landing gear braking system. Secondly, the paper proposes enhancements to the system specification model to enable functional hazard assessment and to capture the results within the system architecture specification model, i.e., using color-coding of system functions according to the severity of their associated failures as a visual aid to the system architect. In addition, the proposed features in the system specification model can help the safety engineer analyze failure relationships better. In summary, the proposed method improves consistency between the system architect and the safety expert in making safety-informed architecting decisions early in the development process, improving its effectiveness.

MIGRATING TO ARP4754A: TAILORING OF ARCHITECTURE AND SYSTEMS REQUIREMENTS DEFINITION PROCESSES IN THE ROTORCRAFT INDUSTRY

AbstractRotorcrafts are very complex systems that require a huge systems engineering effort to design, implement and integrate. A successful aircraft design is a matter of good integration between engineering disciplines and suppliers just as much as it is about finding a good technical solution to the customers' expectations. This issue is well understood within the industry and competent authorities. Companies now face the challenge of transitioning from integrating complex systems to make an aircraft (as per ARP4754) to engineering and collating a complex aircraft system as per ARP4754A: in other words, the focus shifted to a more holistic view to the aircraft development, a game changer in all respects. Leonardo Helicopters is tailoring its internal processes to reflect this change and challenge. While the ideal process can be defined today, the transition takes time and a significant change in culture and organization needs to take place. To support the transition, the authors have developed a hybrid approach to the aircraft architecture and system requirements definition process. This new approach leverages existing expertise at a system level to facilitate the integration between systems and the subsequent migration to bridge the gap with the aircraft engineering activities required by the ARP4754A.

A Semi-Supervised Siamese Network for Complex Aircraft System Fault Detection with Limited Labeled Fault Samples

Aircraft onboard systems typically have limited labeled fault samples and large amounts of unlabeled data. To better utilize the information contained in limited labeled fault samples, a deep learning-based semi-supervised fault detection method is proposed, which leverages a small number of labeled fault samples to enhance its performance. A novel sample pairing strategy is introduced to improve algorithm performance by iteratively utilizing fault samples. A comprehensive loss function is employed to accurately reconstruct normal samples and effectively separate fault samples. The results of a case study using real data from a commercial aircraft fleet demonstrate the superiority of the proposed method over existing techniques, with improvements of approximately 16.7% in AP, 9.5% in AUC, and 19.2% in F1 score. Ablation studies confirm that performance can be further improved by incorporating additional labeled fault samples during training. Furthermore, the algorithm demonstrates good generalization ability.

Analysing Mission-critical Cyber-physical Systems with AND/OR Graphs and MaxSAT

Cyber-Physical Systems (CPS) often involve complex networks of interconnected software and hardware components that are logically combined to achieve a common goal or mission; for example, keeping a plane in the air or providing energy to a city. Failures in these components may jeopardise the mission of the system. Therefore, identifying the minimal set of critical CPS components that is most likely to fail, and prevent the global system from accomplishing its mission, becomes essential to ensure reliability. In this article, we present a novel approach to identifying the Most Likely Mission-critical Component Set (MLMCS) using AND/OR dependency graphs enriched with independent failure probabilities. We address the MLMCS problem as a Maximum Satisfiability (MaxSAT) problem. We translate probabilities into a negative logarithmic space to linearise the problem within MaxSAT. The experimental results conducted with our open source tool LDA4CPS indicate that the approach is both effective and efficient. We also present a case study on complex aircraft systems that shows the feasibility of our approach and its applicability to mission-critical cyber-physical systems. Finally, we present two MLMCS-based security applications focused on system hardening and forensic investigations.

Applications of deep learning in big data analytics for aircraft complex system anomaly detection

Big data analytics with deep learning approach have attracted increasing attention in transportation engineering, involving operations, maintenance, and safety. In commercial aviation sectors, operational, and maintenance data produced on modern aircraft is increasing exponentially, and predictive analysis of these data is an exciting and promising field in aviation maintenance, which has a potential to revolutionize aerospace maintenance industry. This study illustrates the state-of-the-art applications of deep learning in big data analytics for predictive maintenance and a real-world case study for commercial aircraft. A Long Short-Term Memory network based Auto-Encoders (LSTM-AE) is proposed for complex aircraft system fault detection and classification, which makes use of the raw time-series data from heterogeneous sensors. The proposed method uses nominal time-series samples corresponding to healthy behavior of the system to learn a reconstruction model based on LSTM-AE framework. Then the system health index (HI) and fault feature vectors are derived from the reconstruction error matrix for fault detection and classification. The proposed method is demonstrated on a real-world data set from a commercial aircraft fleet. The typical PCV faults as well as the 390 F sensor and 450 F sensor faults due to sense line air leakage are successfully detected and distinguished based on the extracted features. The case study results show that the computed HI can effectively characterize the health state of the aircraft system and different fault types can be identified with high confidence, which is helpful for line fault troubleshooting.

Human reliability increasing approach in aircraft maintenance technician’s training process

This article presents an approach for increasing the maintenance technician’s reliability by considering the human fault rate as utility function’s maximization problem in the technician’s training process. Adequately trained technicians are capable to perform a maintenance and manage the reliability of their assigned assets within the complex aircraft systems. In general, a degradation of aircraft reliability, due to maintenance tecnician’s competency, typically leads to significant, undesirable safety and economic consequences. In this article, an optimal control theory is applied on the purpose of finding of a fault rate reduction series in the training process which leads to highest technician’s reliability in the maintenance process of the complex aircraft systems.

Using requirement-functional-logical-physical models to support early assembly process planning for complex aircraft systems integration

The assembly line process planning connects product design and manufacturing through translating design information to assembly integration sequence. The assembly integration sequence defines the aircraft system components installation and test precedence of an assembly process. This activity is part of the complex systems integration and verification process from a systems engineering view. In this paper, the complexity of modern aircraft is defined by classifying aircraft system interactions in terms of energy flow, information data, control signals and physical connections. At the early conceptual design phase of assembly line planning, the priority task is to understand these product complexities, and generate the installation and test sequence that satisfies the designed system function and meet design requirements. This research proposes a novel method for initial assembly process planning that accounts for both physical and functional integrations. The method defines aircraft system interactions by using systems engineering concepts based on traceable RFLP (Requirement, Functional, Logical and Physical) models and generate the assembly integration sequence through a structured approach. The proposed method is implemented in an industrial software environment, and tested in a case study. The result shows the feasibility and potential benefits of the proposed method.

Integrated Reasoning Framework for Vehicle Level Diagnosis of Aircraft Subsystem Faults

A framework for integrated diagnostic reasoning to detect and isolate faults in complex aircraft systems, at the vehicle level, is proposed. A Digital Twin emulating the functions of an aircraft’s selected subsystems is to be developed; this will include their input/output parameters connecting to other systems, for simulating the subsystem level interactions. The failure propagation across subsystems will be observed by injecting different faults. A diagnostic module for each subsystem will detect and isolate faults. This will be complemented by an integrated reasoner at the vehicle level which will isolate the root cause of propagated faults. On successful completion, the fully developed integrated reasoner shall distinguish an effect (for example, engine power reduction in B777 (Sleight and Carter, 2014)) from its root cause (blocked Fuel Oil Heat Exchanger (Sleight and Carter, 2014)), yielding maintenance savings and increasing dispatch reliability.

Failure and failure characterization of QFP package interconnect structure under random vibration condition

Electronics installed in modern complex systems, like automotive and aircraft systems, are mainly subjected to mechanical vibrations in applications. The interconnection structure, as the mechanical fixing and electrical interconnection between the electrical device and the printed circuit board, is a key part in electronics. Presently, there are few researching articles on reliability of QFP interconnect structure under random vibration. In this paper, eight specimens of QFP100 with the self-testing real-time circuit have been tested to failure by subjecting to a narrow-band random vibration at its first natural frequency. The charging time of external capacitor in the self-test circuit has been extracted as the monitoring signal. Failure modes of interconnect structure have been analyzed in statistics. Then, the relationship between the monitoring signal and interconnect failure has been investigated. Finally, failure data, conforms to a two-parameter Weibull distribution, has been used to establish the life distribution of interconnect structure. Results show that there are four failure modes and three failure places in interconnect structure under random vibration, which is consistent with simulation results by FEM, and the charging time can characterize the failure and failure process of interconnect structure well.

UTILIZING MBSE PATTERNS TO ACCELERATE SYSTEM VERIFICATION

ABSTRACTIn aerospace, automotive, healthcare, and other domains, the capability to effectively plan and perform system verification tests is increasingly a strategic differentiator. This paper reports on methods used to improve effectiveness of complex aircraft system tests, the gains achieved, and their connection to underlying methods and trends. These include use of model‐based systems engineering (MBSE), leveraged by pattern‐based systems engineering (PBSE) to generate configurable, reusable system models — the focus of the INCOSE MBSE Patterns Challenge Team (Patterns Challenge Team 2013‐2015). Distinctive aspects include (1) use of configurable, model‐based patterns of system descriptions, including configurable system verification tests, (2) improved ability of model‐based descriptions to integrate modeling tools and automated systems for test management, (3) use of models to describe both the system under development and the development process, and (4) ability of these models to be integrated with other system lifecycle management processes and information systems, for increased leverage.

Model-based safety analysis of a control system using Simulink and Simscape extended models

The aircraft or system safety assessment process is an integral part of the overall aircraft development cycle. It is usually characterized by a very high timely and financial effort and can become a critical design driver in certain cases. Therefore, an increasing demand of effective methods to assist the safety assessment process arises within the aerospace community. One approach is the utilization of model-based technology, which is already well-established in the system development, for safety assessment purposes. This paper mainly describes a new tool for Model-Based Safety Analysis. A formal model for an example system is generated and enriched with extended models. Then, system safety analyses are performed on the model with the assistance of automation tools and compared to the results of a manual analysis. The objective of this paper is to improve the increasingly complex aircraft systems development process. This paper develops a new model-based analysis tool in Simulink/Simscape environment.

Utilizing MBSE Patterns to Accelerate System Verification

AbstractIn aerospace, automotive, health care, and other domains, the capability to effectively plan and perform system verification tests is increasingly a strategic differentiator. This paper reports on methods used to improve effectiveness of complex aircraft system tests, the gains achieved, and their connection to underlying methods and trends. These include use of Model‐Based Systems Engineering (MBSE), leveraged by Pattern‐Based Systems Engineering (PBSE) to generate configurable, re‐usable system models‐‐the focus of the INCOSE MBSE Patterns Challenge Team. (Patterns Challenge Team, 2013‐2015)Distinctive aspects include (1) use of configurable, model‐based patterns of system descriptions, including configurable system verification tests, (2) improved ability of model‐based descriptions to integrate modeling tools and automated systems for test management, (3) use of models to describe both system under development and the development process, and (4) ability of these models to be integrated with other system life cycle management processes and information systems, for increased leverage.

Real-time effects of normobaric, transient near-anoxia on performance.

Recent physiological incidents involving pilots of high performance fighter aircraft have raised the question of whether inadvertent, short bursts of significantly reduced oxygen could negatively impact real-time performance. This study evaluated normobaric, real-time performance in the setting of transient near-anoxia to inform future countermeasure development. The study was performed on 12 healthy subjects without significant medical history. Following collection of baseline data, real-time performance changes were evaluated during sequentially increasing periods of near-anoxic gas exposure (F(I)0(2) = 1%) using a computer-based performance assessment tool. Both room air and 100% oxygen were used as the prebreathe/recovery gases. Statistical analysis was performed on the results. Under normobaric conditions, subjects inspiring up to five near-anoxic breaths showed no significant performance decrement in either accuracy or effective actions per minute. Mean accuracy up to five near-anoxic breaths was 0.67 (SD = 0.01) as compared to a baseline mean of 0.68 (SD = 0.02). Hyperoxia had a protective effect on subject physiological response to near anoxia. These normobaric findings offer an assessment of real-time performance changes in the setting of transient, near-anoxic gas exposure. Overall, the results help inform the design of increasingly complex aircraft oxygen delivery systems in terms of how tightly such systems must match the sea-level gas equivalent with increasing altitude. This is particularly relevant as such systems are being called upon to ensure safe aircrew operations across an expanding operational flight envelope.

Lessons from aviation safety: "plan your operation - and operate your plan!".

Lessons from aviation safety: "plan your operation - and operate your plan!".

Technology assessment for a complex aircraft system using technology scenarios

Military decision makers need to understand and assess the benefits and consequences of their decisions in order to make cost efficient, timely, and successful choices. Technology selection is one such critical decision, especially when considering the design or retrofit of a complex system, such as an aircraft. An integrated and systematic methodology that will support decision making between technology alternatives and options while assessing the consequences of such decisions is a key enabler. This paper demonstrates, through application to a notional medium-range short takeoff and landing aircraft, one such enabler: the Technology Impact Forecasting (TIF) method. The goal of the TIF process is to explore both generic, undefined areas of technology, as well as specific technologies, and assess their potential impacts. This is actualized through the development and use of technology scenarios, and allows the designer to determine where to allocate resources for further technology definition and refinement, as well as provide useful design information. The paper particularly discusses the use of technology scenarios and demonstrates their use in the exploration of seven technologies of varying Technology Readiness Levels.

The mutual influence of aircraft aerodynamics and ship hydrodynamics in theory and experiment

As early as 1784, sharp-eyed engineers and scientists noted striking similarities between the dynamics of seagoing vessels and aerial vehicles. By the early twentieth century, naval engineers and scientists were developing and designing airplanes and dirigibles using empirical principles derived from naval architecture. Several key researchers in aerodynamics began their career as naval architects (David A. Taylor, William F. Durand and Jerome C. Hunsaker) and carried out their experiments in ship testing facilities. By the 1930s, however, the transfer of knowledge was irrevocably reversed as empiricism gave way to more fundamental, physics-based research. The rapid evolution of complex aircraft systems and flight envelopes led to new theoretical developments in aerodynamics and maneuvering, which quickly found their way into naval ship design. The theoretical and experimental results for airfoils, rigid airships and fixed-wing aircraft developed by Ludwig Prandtl, Theodore von Karman, Max M. Munk and Hilda M. Lyon were employed in the hydrodynamic development of surface ships and submarines. This paper examines how the ideas, concepts and data from one discipline influenced the other and explores the processes by which that knowledge was transferred between disciplines.

Efficient Certification of Highly Integrated and Complex Aircraft Systems, Such as Integrated Modular Avionics

Efficient Certification of Highly Integrated and Complex Aircraft Systems, Such as Integrated Modular Avionics

Human Systems Integration

Effective Human Factors Engineering (HFE) has provided the aerospace industry with design considerations that promote aviation safety in the development of complex aircraft systems, as well as the operators and maintainers that utilize those systems. HFE is an integral aspect within the systems engineering process. Measuring the effectiveness of Human Systems Integration (HSI) in the research & development stage is critical for the design of new and modified systems. This paper focuses on the importance of design and integration in the product development stages as well as understanding the impact on the user population.

System Dependency Analysis as a Common Cause Search Engine for Complex Aircraft Systems

System Dependency Analysis as a Common Cause Search Engine for Complex Aircraft Systems

System Dependency Analysis Supporting Common Cause Analyses of Complex Aircraft Systems

System Dependency Analysis Supporting Common Cause Analyses of Complex Aircraft Systems