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Automatic Dependent Surveillance Broadcast (ADS-B) is envisioned to support seamless aircraft surveillance and enhanced air-to-air and air-to-ground applications. ADS-B is an integrated system, dependent on on board navigation systems to obtain aircraft state information as well as a communication data link to broadcast this information to Air Traf...
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... the second step, a high-level system architecture diagram (Figure 2), ADS-B OUT functional block diagram ( Figure 3) and ADS-B IN functional block diagram ( Figure 4) are developed based on input from a literature review and expert input (particularly from Airbus, NATS and British Airways). The system architecture in Figure 2 is divided into five levels: Level-0 indicates the Global Navigation Satellite Figure 1. ADS-B failure mode identification ...
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... the second step, a high-level system architecture diagram (Figure 2), ADS-B OUT functional block diagram ( Figure 3) and ADS-B IN functional block diagram ( Figure 4) are developed based on input from a literature review and expert input (particularly from Airbus, NATS and British Airways). The system architecture in Figure 2 is divided into five levels: Level-0 indicates the Global Navigation Satellite Figure 1. ADS-B failure mode identification ...
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... ( In the third step, ADS-B failure modes are identified from safety reports by ANSPs on ADS-B trial implementations, an extensive literature review on the system components and ADS-B report performance analysis. For further details of the ADS- B report performance analysis, refer to (Ali et al., 2013c, Ali et al., 2013a) 2013a). The scope of the analysis in this paper is from Level-0 to Level-4 as shown in Figure 2. Most of the failure modes in Level-0 (GNSS) included in the paper are adopted from existing research (Bhatti andOchieng, 2007, Ochieng andSauer, 2003 ...
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With the growth of commercial aviation over the last few decades there have been many applications designed to improve the efficiency of flight operations as well as safety and security. A number of these applications are based on the gathered data from flights; the data is usually acquired from the various sensors available on the aircraft. There...
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... Due to the degradation brought on by the environment, age, no maintenance, or the demand to adhere to current design standards, it is essential to retrofit existing concrete infrastructure [1][2][3][4][5]. As RC infrastructure ingredients were widely used for decades in developed countries, these issues mainly affect them [6][7][8][9][10]. Destroying deteriorated buildings is not a lengthy solution and is also expensive. ...
Construction repairs have used fiber-reinforced cement mortar (FRCM). Concrete and FRCM bond strength usually outweigh mechanical criteria. Nevertheless, testing complex bonds like the FRCM and concrete bond takes time, money, and errors. This study employed fuzzy logic (FL) based on the adaptive neuro-fuzzy inference system (ANFIS) to simplify and reliably estimate the FRCM-to-concrete bond strength (CBS) by modeling complicated and non-linear systems computationally efficiently. The models take six inputs: concrete splice length, stirrup cross-sectional area to spacing, longitudinal tension bar area to effective cross section, compressive strength, relative rib area, and minimum concrete cover. The model outputs concrete steel bar bond strength. The FLANFIS model predicts FRCM-to-CBS using the tensile testing results of the 10 specimens (5 concrete and 5 FRCM). Data instruct the model and measure its precision. This article defines the ANFIS-based FRCM-to-CBS. This research will employ 5 concrete specimens and 5 FRCM specimens, totaling 0.05 m^3 of concrete and FRCM mix. 0.25 kg of adhesive bonds the sample. Grip, control, and data gathering systems are employed with a 1 kN tensile testing equipment. This research comprises preparing concrete and FRCM specimens, bonding with adhesive, and tensile testing. The FL-ANFIS model predicts FRCM-to-CBS with a high coefficient of determination (R2) of 0.995 and a strong correlation coefficient (r) of 0.982 in training. The pattern predicted accurately with RMSE of 0.264 and MAE of 0.196. This paper shows that FL-ANFIS can predict steel bar bond strength in concrete quickly and accurately. The pattern reduces waste, design costs, and time.
... On the one hand, critical concerns like the potential weaknesses and their probable causes, as well as their possible downsides on the Air Traffic Control (ATC) operating state of the ADS-B technology have been explored [7]. On the other hand, considering the fact ADS-B messages volume is increasing constantly since there is an increment trend in the number of aircraft installed with ADS-B facilities [8,9]. ...
This paper provides research on the enhanced NextGen ADS-B reception method and its performance in laboratory and flight tests. It sheds the light on end-to-end reception techniques to comply with key requirements. ADS-B has emerged as among the most intriguing avionics for both researchers and companies since the launch of NextGen in 2009. ADS-B provides authorities with a mechanism for use in continuously monitoring the position and track of an airplane using periodic and independent broadcast messages that transmit Global Navigation Satellite System (GNSS) position information. The enhanced pulse detection technique is used to detect and validated preamble pulses. Besides the utilization of multiple amplitude samples technique not only improve bit and confidence declaration accuracy but also make it capable of deploying error detection/correction algorithms which are two aspects of enhanced Extended Squitter reception. In addition, applying a slow attack automatic gain control (AGC) algorithm improves system sensitivity and performance. The implementation is done in MATLAB Simulink and C++. Software Defined Radio (SDR) module, BladeRF, is used programable platform for the communication system. Subsequently, the lab experimental and flight test results show that when applying these strategies in a real environment, significant performance is achievable.
... The necessity for retrofitting existing concrete infrastructure is essential due to ageing, environmental-induced degradation, lack of maintenance, or the need to fulfill current design standards [1]. Developed countries are mainly affected due to the above-mentioned issues, where RC infrastructure components were being used for decades [2][3][4]. The demolition of deteriorated structures is not a sustainable solution, and it is also expensive. ...
Fibre-reinforced cement mortar (FRCM) has been widely utilised for the repair and restoration of building structures. The bond strength between FRCM and concrete typically takes precedence over the mechanical parameters. However, the bond behaviour of the FRCM–concrete interface is complex. Due to several failure modes, the prediction of bond strength is difficult to forecast. In this paper, effective machine learning models were employed in order to accurately predict the FRCM–concrete bond strength. This article employed a database of 382 test results available in the literature on single-lap and double-lap shear experiments on FRCM–concrete interfacial bonding. The compressive strength of concrete, width of concrete block, FRCM elastic modulus, thickness of textile
layer, textile width, textile bond length, and bond strength of FRCM–concrete interface have been taken into consideration with popular machine learning models. The paper estimates the predictive accuracy of different machine learning models for estimating the FRCM–concrete bond strength and found that the GPR model has the highest accuracy with an R-value of 0.9336 for interfacial bond strength prediction. This study can be utilising in the estimation of bond strength to minimise the experimentation cost in minimum time.
... Although adequate performance standards were established for various surveillance equipment, to date the impacts of surveillance system failures in terms of separation degradation, specifically in the UAS platform, have not been defined. Moreover, traditional radar and Mode-A/C transponder technologies show inherent deficiencies in different airspace and equipage scenarios especially in the presence of high air traffic densities [25][26][27][28][29][30][31][32][33]. The failure modes for different cooperative sensors such as Mode S, TCAS, ADS-B are well defined and safety assessments have been carried out on the individual surveillance sensor considering functions in the manned aircraft. ...
The airworthiness certification of aerospace cyber-physical systems traditionally relies on the probabilistic safety assessment as a standard engineering methodology to quantify the potential risks associated with faults in system components. This paper presents and discusses the probabilistic safety assessment of detect and avoid (DAA) systems relying on multiple cooperative and non-cooperative tracking technologies to identify the risk of collision of unmanned aircraft systems (UAS) with other flight vehicles. In particular, fault tree analysis (FTA) is utilized to measure the overall system unavailability for each basic component failure. Considering the inter-dependencies of navigation and surveillance systems, the common cause failure (CCF)-beta model is applied to calculate the system risk associated with common failures. Additionally, an importance analysis is conducted to quantify the safety measures and identify the most significant component failures. Results indicate that the failure in traffic detection by cooperative surveillance systems contribute more to the overall DAA system functionality and that the probability of failure for ownship locatability in cooperative surveillance is greater than its traffic detection function. Although all the sensors individually yield 99.9% operational availability, the implementation of adequate multi-sensor DAA system relying on both cooperative and non-cooperative technologies is shown to be necessary to achieve the desired levels of safety in all possible encounters. These results strongly support the adoption of a unified analytical framework for cooperative/non-cooperative UAS DAA and elicit an evolution of the current certification framework to properly account for artificial intelligence and machine-learning based systems.
... Failure modes analysis is often a first step in the evaluation of a device architecture to determine ways in which a system can fail. In [1], Ali et al. provide a comprehensive analysis of the ADS-B system, identifying 65 failure modes categorized by different root causes, viz., device failure, human error, and environmental effects. The device-centric analysis of the system by Ali et al. exhaustively explores the entire failure space of ADS-B. ...
... As shown in Fig. 7, each manifestation corresponds to one or more simulation models. In [1], Ali et al. discusses five failure models for incorrect ADS-B state data, viz., step error, ramp error, random noise, oscillation and bias. This model, however, does not account for the safety checks discussed in Section 4. For instance, bias and oscillation errors are caused by faulty sensor measurements, which would automatically be captured in the assigned navigation accuracy categories before being broadcast. ...
... A fault in a received ADS-B message may result from a fault in data sources (e.g., GPS receiver), ADS-B transponders, or process for disseminating data. A comprehensive analysis of the different failure modes is discussed in [1], while [11] includes our previous work on an ADS-B fault summary and mathematical notation for an agent-based model including fault detection and isolation. Faults in an avionics technology may result in a propagating effect on other devices, and a full recovery of system functions is not always possible. ...
... ICAO's ADS-B performance monitors have recorded such faults during civil aviation operations [9], [10], which includes faulty GPS, inaccurate encoding at the ADS-B, or accumulated error due to projection of data to compensate latent or dropped messages. In [1], state information errors manifest as (a) step, (b) ramp, (c) random noise, (d) bias, and (e) oscillation. In Section V, the simulation scenario includes a persistent fault of a +0.05 deg bias in longitude in a transmitted ADS-B message. ...
... The connection between the top event and basic events are illustrated using logic gates ( Henley and Kumamoto, 1981). Before constructing the fault trees, a detailed understanding of the ADS-B In and ADS-B Out system architectures and functionalities was gained from the literature and subject matter experts from NATS and British Airways ( Syd Ali et al., 2014). Figures 1 to 6 illustrate the fault trees constructed for the potential hazards for the ADSB system. ...
... In the case where the failure modes are not detected, this may lead to safety risks. Based on the findings from the failure modes ( Syd Ali et al., 2014), six potential hazards of the ADS-B system are identified. FTA is used to develop and quantify the occurrence of the potential hazards (risk). ...
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).
... Input for this task is obtained from literature reviews, safety reports and from the PBSA. The failure mode identification for ADS-B system is conducted by the author in (Ali et al., 2014). The results are in the form of a comprehensive failure mode register for ADS-B system. ...
... Based on the impact of failure modes identified in (Ali et al., 2014), potential hazards for the ADS-B system are identified and defined as tabulated in Table 3. ...
... It also identifies the system failure modes and risks related to the system implementation, and proposes mitigation measures to reduce the identified risks. The framework has been applied to a safety case for ADS-B system trial implementation in the London Terminal Manoeuvring Area (LTMA) (Ali et al., 2014(Ali et al., , 2013b) as a sole surveillance system. The framework assessed the system's operational performance (in terms of accuracy, integrity, update rate and latency) and failure modes respectively. ...
The ATM system is currently undergoing various fundamental changes to improve air travel performance. A key change is the transition from a mainly reactive and tactical system to a significantly more predictive and strategic system. This is encapsulated in the concept of 4D trajectory based operations, currently being developed in Europe and the USA through the Single European Sky (SES)/Single European Sky ATM Research (SESAR) and the Next Generation Air Transportation System (NextGEN) respectively. At the core of this transition, is the need for improved situational awareness, shared between relevant stakeholders. The Automatic Dependent Surveillance Broadcast (ADS-B) system is a key enabler of this concept, targeted at distributing real-time positioning and navigation information to stakeholders. Therefore, the safety and credibility of the ADS-B system to support various ground and airborne applications are key, and need to be assessed and validated. This paper reviews existing safety assessment methods, identifies key limitations and proposes a novel, comprehensive and rigorous safety assessment framework for the ADS-B system.
Automatic Dependent Surveillance—Broadcast (ADS-B) is an emerging means of aeronautical surveillance for air traffic control. Aircraft periodically broadcast positional updates to ground stations. Although ADS-B outperforms traditional radars in terms of accuracy and update rate, positional verification—a technique used to check the validity of the position report—is necessary to counter anomalies. In this study, two different methods were compared when the ground stations measure time difference of arrival (TDOA). One is direct; the test statistic is essentially the difference between the measurement and a prediction calculated from the position report. Another method is multilateration (MLAT)-based and two-step; the emitter position is firstly estimated, whereupon the difference between the estimated and reported positions constitutes the test statistic. As a result of the comparison, a performance difference, which depending on the number of receivers, was revealed. This is an useful suggestion for implementing ADS-B when the existing multilateration infrastructure is exploited.
