Browsing by Author "Place, Simon"

Now showing 1 - 9 of 9
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    Bayesian model for strategic level risk assessment in continuing airthworthiness of air transport
    (Cranfield University, 2010) Jayakody-Arachchige, Dhanapala; Place, Simon; Snow, John
    Continuing airworthiness (CAW) of aircraft is an essential pre-requisite for the safe operation of air transport. Human errors that occur in CAW organizations and processes could undermine the airworthiness and constitute a risk to flight safety. This thesis reports on a generic Bayesian model that has been designed to assess and quantify this risk. The model removes the vagueness inherent in the subjective methods of assessment of risk and its qualitative expression. Instead, relying on a transparent, structured mathematical process based on Bayes’ Theorem of conditional probabilities, the model yields a quantitative risk output expressed as a probability of error coupled with a probability of consequence based on data. The Bayesian model has 184 nodes and 1138 parameters that define causal factors for error against which data is collected as either beliefs or evidence, the latter returning more reliable results. Beliefs could be gradually replaced with evidence as they become available, improving fidelity. The generic model can be modified by adding or truncating parameters to suit conditions applicable to specific organizations or similar groups. The model was validated using field data from a cargo operator using large western jet freighters, covering 34,338 sectors of which 193 carried human error. Separate tests were performed simulating the operator’s belief that it was operating to global standards. The output for belief was consistent with global and UK flat rate safety levels, achievable if the operator flew 3M and 6M sectors respectively according to their belief. However, the output from evidence returned a risk level more severe than the belief, partly driven by the allowance for unknowns built into the computing technique and part by the relatively small number of sectors considered. In “what-if” prediction mode the model calculates the change in risk level due to new errors, and through sensitivity analysis it can identify and rank performance indicators. In CAW organizations subjected to Risk Based Oversight (RBO) concept and ICAO mandate on Safety Management System (SMS), the model can set risk threshold levels for individual organizations, to measure variations, and by continuous updating, to monitor safety performance at strategic level. Sharing data and with agreed performance levels, the Regulator and operators should be able negotiate an oversight plan. Using the model pro-actively, the organization could exercise a degree of self-regulation, thereby accruing cost benefits through reduced Regulator oversights.
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    Human Factors Effects in Helicopter Maintenance: Proactive Monitoring and Controlling Techniques
    (Cranfield University, 2010) Rashid, Hamadalneel Suliman Jumaa; Braithwaite, Graham R.; Place, Simon
    Aviation maintenance errors account for between 13% and 23% of the global aviation incidents and accidents initiators, which require a wider global use of aviation maintenance safety improvement activities. The current research applies the Human Error Risk Management in Engineering Systems (HERMES) methodology that conceptualizes two main streams of study. These are the retrospective investigation of human errors within aviation maintenance contexts, and a prospective innovation of new tools that work to prevent errors occurring. In this research the impact of human reliability on aviation maintenance safety is investigated. Rotorcraft is taken as a focal case study. A new model to represent the accumulation of crucial maintenance human errors causal factors, within aviation maintenance companies, is introduced. A total of 804 recent maintenance-induced helicopter accidents were reviewed, from which 58 fatal accidents and serious incidents were thoroughly analysed using Human Factors Accident Classification System - Maintenance Extension (HFACS-ME). A 4th order of analysis is newly introduced into the HFACS-ME taxonomy under the notion of ‘Specific Failures’ for better analysis resolution and comprehensiveness. Hypothesizing that human factors errors within aviation maintenance industry can be more effectively managed by applying proactive monitoring and early error detecting techniques - at both organizational and individual levels, a proactive Aviation Maintenance Monitoring Process (AMMP) is formulated. AMMP is a holistic hybrid retrospective / prospective integrated process that is to be simultaneously and collectively implemented by main industry stake-holders - regulators, manufacturers and maintenance organisations. The aim is to proactively monitor the existence of human error causal factors that are initiated during design practices, manufacturing processes, or at later stages due to workplace conditions. As a result, such causal factors can be gradually eliminated to reduce the overall risk of maintenance errors. This generic AMMP model is based on a Root Cause Existence Scale (RCES) and a comprehensive sociotechnical user program, coded as ‘ErroDetect’, built applying the fuzzy Analytic Network Process (fuzzy ANP) theory. A total of 870 different assessment criteria were designed and then in-built within the software thus mapping the outcomes of the retrospective error causal factors investigative studies. Full simulation of the process is conducted, and then it was further validated practically in real world within industry for both design for maintainability within major rotorcraft manufacturer facilities, and for MRO’s performance safety enhancement. Validation results were thoroughly discussed. The AMMP is found to have significantly enhanced aircraft maintenance proactive safety for both designers and maintainers. The tool can also be adopted for regulation purposes.
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    Is there a link between no fault found and airworthiness?
    (Cranfield University, 2023) Lacey, Laura; Saddington, Alistair J.; Place, Simon
    The no fault found phenomenon negatively impacts the aviation industry and an aircraft’s airworthiness. Airworthiness and no fault found must be appreciated during the design, maintenance and subsequent operation. This research aimed to establish if a link between no fault found and airworthiness exists and to garner the aircrew's perception of any possible link. Semi-structured interviews and a questionnaire were conducted to generate primary data. Pilots and aircraft accident investigator interviews were conducted to establish a foundation of knowledge, experience and perspectives on no fault found and airworthiness to support the questionnaire. The questionnaire established predominately RAF aircrew views on the impact of no fault found on airworthiness, the key aircraft systems affected, communication methods and associated training completed. Secondary data from an aviation company’s maintenance records were analysed for no fault found frequencies. The research analysis includes systems engineering, Bowtie, Functional Resonance Analysis Method and fuzzy logic inference. The RAF aircrew canvassed perceives no fault found to negatively impact airworthiness causing missions to be cancelled, curtailed or replanned. Trust between RAF aircrew and engineers is diminished. This impacts the analysis and recording of no fault found and airworthiness. Training the aircrew and engineers on how to conduct the post-sortie engineering debrief, in a dedicated location, whilst using a dedicated proforma that focuses on no fault found and airworthiness, and reviewing the aircraft’s no fault found history will decrease the occurrences of the phenomenon. An iterative relationship between Bowtie and Functional Resonance Analysis Method established the key aspects that impact the link between no fault found and airworthiness. Based on mission success, the fuzzy logic inference of the aircrew and RAF engineers’ linguistic variables, (negligible to severe), that described the aircraft’s airworthiness level as a consequence of repeated no found faults, were combined to create 3-dimensional surface plots to represent the aircraft’s overall airworthiness level. These combined confirmed that airworthiness is not binary. These original 3-dimensional surface plots indicate the no fault found/airworthiness relationship varies over longer periods but is most pronounced in shorter periods with more no fault found occurrences. This indicates that the current methods for analysing and assessing the impact of no fault found on airworthiness require redefining and this research suggests that no fault found /Airworthiness working groups with key stakeholders are a means to achieve this. As the questionnaire participants were mainly RAF aircrew the external validity for them has been established. However, the wider validity of this research with other aviation organizations cannot be stated categorically unless further research is conducted.
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    Landing gear health assessment: synergising flight data analysis with theoretical prognostics in a hybrid assessment approach
    (PHM Society, 2024-06-27) El Mir, Haroun; King, Stephen; Skote, Martin; Alam, Mushfiqul; Place, Simon
    This study addresses a critical shortfall in aircraft landing gear (LG) maintenance: the challenge of detecting degradation that necessitates intervention between scheduled maintenance intervals, particularly in the absence of hard landings. To address this issue, we introduce a Performance Degradation Metric (PDM) utilising Flight Data Recorder (FDR) output during the touchdown and initial roll phases of landing. This metric correlates time-series accelerometer data from a Saab 340B aircraft’s onboard sensors with non-linear response dynamic models that predict expected LG travel and reaction profiles across a set of ground contact cycles within a single landing. This facilitates the early detection of deviations from standard LG response behaviour, pinpointing potential performance abnormalities. The initiator of this approach is the Landing Sequence Typology, which systematically decomposes each aircraft landing into successive dynamic periods defined by their representative boundary conditions. What follows is the setting of initial parameters for the ordinary differential equations (ODE)s of motion that determine the orientation and impact responses of the most critical components of the LG assembly. Solving these ODEs with the integration of a non-linear representation of an oleo-pneumatic shock absorber model compliant with CS25 aircraft standards produces anticipated profiles of LG travel based on factors such as aircraft weight and speed at touchdown, which are subsequently cross-referenced with real accelerometer data, enhanced by video footage analysis. This footage is crucial for verifying the sequence of LG touchdowns and corresponding accelerometer outputs, thereby bolstering the precision of our analysis. Upon the conclusion of this study, by facilitating the early identification of LG performance deviations in specific landing scenarios, this diagnostic tool shall enable timely maintenance interventions. This proactive approach not only mitigates the risk of damage escalation to other components but also transitions main LG maintenance practices from reactive to proactive.
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    Modelling, simulation and verification of the Saab 340B
    (AIAA, 2023-01-19) Makadia, Jeet; Millidere, Murat; Alam, Mushfiqul; Place, Simon; Whidborne, James F.
    Flight simulation modelling of an aircraft is required for various purposes including performance analysis, flight control design, and flying qualities analysis. The Saab 340B is a twin turboprop transport aircraft designed to seat 30-36 passengers. A Saab 340B has been modified to operate as a flying laboratory for teaching and research purposes at the Cranfield University, United Kingdom. This paper demonstrates a component build-up approach towards creating a simulation model using the data available from the aircraft manufacturer. This approach has previously proven successful in establishing the fundamental working principles of flight dynamics for a Jetstream J31 aircraft. Empirical estimates of the aerodynamic forces and moments acting on the aircraft are calculated from the aircraft’s geometrical parameters using Engineering Sciences Data Unit (ESDU) data sheets. The contribution of this study is a systematic approach to developing an aerodynamic model using ESDU and comparing the results with the collected flight test data across the entire flight envelope for the aircraft.
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    Reliability model for helicopter main gearbox lubrication system using influence diagrams
    (Elsevier, 2015-02-19) Rashid, Hamad; Place, Simon; Mba, David; Keong, R. L. C.; Kleine-Beek, Werner; Romano, M.
    This paper presents the development of a model to assess the reliability of helicopter main gearbox (MGB) lubricating systems. The loss of oil from a helicopter MGB will lead to increased friction between components, a rise in component surface temperatures, and subsequent mechanical failure of gearbox components. A number of significant helicopter accidents have been caused due to such loss of lubrication. Current certification requirements for Category A helicopters require that gearboxes which use pressurized lubrication systems must show a capability to continue operation for a period of 30 minutes after suffering a loss of oil. This paper reports on methods for assessing reliability of pressurized MGB lubrication systems. Safety risk modeling was conducted for MGB oil system related accidents and incidents in order to analyse the key failure mechanisms and the contributory factors. As such, the dominant failure modes for lubrication systems and key contributing components were identified. The Influence Diagram (ID) approach was then employed to investigate reliability issues of the MGB lubrication systems at the level of primary causal factors. Early indications show significant benefits from this approach where multiple influences would render alternative approaches overly complex. The ID tool can systematically investigate complex context of events, conditions, and influences that are direct triggers of failures. Within this study, an ID model was introduced to describe the interrelationships between MGB lubrication system failure types. In this way the influence of each of these factors on the overall MGB lubrication system reliability may be assessed.
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    SAAB 340B aerodynamic model development using binary particle swarm optimization
    (AIAA, 2024-01-04) Millidere, Murat; Alam, Mushfiqul; Place, Simon; Whidborne, James
    his paper follows-up previous work on the development of a high-fidelity Saab 340B aerodynamic model using system identification methods. In the prior work, Saab 340B flight tests were carried out using different excitations on the control surfaces. The flight test data was collected at predefined trim points. Thrust forces and moment were obtained using the propeller efficiency map provided by the manufacturer. The equation and output error methods were employed to analyse flight test data to estimate aerodynamic parameters in the time domain. This paper follows-up previous work on the development of a high-fidelity Saab 340B aerodynamic model using system identification methods. In the prior work, Saab 340B flight tests were carried out using different excitations on the control surfaces. The flight test data was collected at predefined trim points. Thrust forces and moment were obtained using the propeller efficiency map provided by the manufacturer. The equation and output error methods were employed to analyse flight test data to estimate aerodynamic parameters in the time domain. The paper extends the work to select independent variables in the equation error method in an optimal way using binary particle swarm to determine the best subset of independent variables. The impact of the hyperparameters of the binary PSO approach such as the transfer function scheme, inertia weight updating strategy, and the value of acceleration coefficients is investigated.
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    Supporting flight dynamics, parameter identification and simulation teaching with a flying classroom
    (Elsevier, 2024-09-05) Whidborne, James F.; Place, Simon; Alam, Mushfiqul; Lu, Linghai
    Cranfield University recently commissioned a modified Saab 340B airliner as a new flying laboratory classroom. The modifications are briefly described before the use of the flying classroom for flight test teaching is described. A flight dynamic model of the aircraft has been developed, and that, along with the data from the flight test programme are extensively used to support masters-level teaching in flight dynamics, flight simulation and flight parameter identification. Some examples of student results are also briefly presented.
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    Using flight data in Bayesian networks and other methods to quantify airline operational risks.
    (Cranfield University, 2019-09) Barry, Simon; Place, Simon
    The risk assessment methods used in airline operations are usually qualitative rather than quantitative, despite the routine collection of vast amounts of safety data through programmes such as flight data monitoring (FDM). The overall objective of this research is to exploit airborne recorded flight data to provide enhanced operational safety knowledge and quantitative risk assessments. Runway veer-off at landing, accounting for over 10% of air transport incidents and accidents, is used as an example risk. Literature on FDM, risk assessment and veer-off accidents is reviewed, leading to the identification of three potential areas for further examination: variability in operational parameters as a measure of risk; measures of workload derived from flight data as a measure of risk; and Bayesian networks. Methods relating to variability and workload are briefly explored and preliminary results are presented, before the main methods of the thesis relating to Bayesian networks are introduced. The literature shows that Bayesian networks are a suitable method for quantifying risk and a causal network for lateral deviation at landing is developed based on accident investigation data. Flight data from over 300,000 flights is used to provide empirical probabilities for causal factors and data for some causal factors is modelled to estimate the probabilities of extreme events. As an alternative to predefining the Bayesian network structure from accident data, a series of networks are learnt from flight data and an assessment is made of the performance of different learning algorithms, such as Bayesian Search and Greedy Thick Thinning. Finally, a network with parameters and structure learnt from flight data is adapted to incorporate causal knowledge from accident data, and the performance of the resulting “combined” network is assessed. All three types of network were able to make use of flight data to calculate relative probabilities of a lateral deviation event, given different scenarios of causal factors present, and for different airports, however the “combined” approach is preferred due to the relative ease of running scenarios for different airports and the avoidance of the lengthy process of modelling data for causal factor nodes. The preferred method provides airlines with a practicable way to use their existing flight data to quantify operational risks. The resulting quantitative risk assessments could be used to provide pilots with enhanced pre-flight briefings and provide airlines with up-to-date risk information of operations to different airports, and enhanced safety oversight.