Aircraft Accident Prevention: Loss-of-Control Analysis

Journal of Guidance, Control, and Dynamics, 2013

Loss-of-Control (LOC) is a major factor in fatal aircraft accidents. Although denitions of LOC remain vague in analytical terms, it is generally associated with ight outside of the normal ight envelope, with nonlinear inuences, and with a signicantly diminished capability of the pilot to control the aircraft. Primary sources of nonlinearity are the intrinsic nonlinear dynamics of the aircraft and the state and control constraints within which the aircraft must operate. This paper examines how these nonlinearities aect the ability to control the aircraft and how they may contribute to loss-of-control. Specically, the ability to regulate an aircraft around stall points is considered, as is the question of how damage to control eectors impacts the capability to remain within an acceptable envelope and to maneuver within it. It is shown that even when a sucient set of steady motions exist, the ability to regulate around them or transition between them can be dicult and nonintuitive, particularly for impaired aircraft. Examples are provided using NASA's Generic Transport Model.

AIAA Guidance, Navigation, and Control Conference, 2014

Aircraft loss of control (LOC) is a leading cause of fatal accidents across all transport airplane and operational classes, and can result from a wide spectrum of hazards, often occurring in combination. Technologies developed for LOC prevention and recovery must therefore be effective under a wide variety of conditions and uncertainties, including multiple hazards, and their validation must provide a means of assessing system effectiveness and coverage of these hazards. This requires the definition of a comprehensive set of LOC test scenarios based on accident and incident data as well as future risks. This paper defines a comprehensive set of accidents and incidents over a recent 15 year period, and presents preliminary analysis results to identify worst-case combinations of causal and contributing factors (i.e., accident precursors) and how they sequence in time. Such analyses can provide insight in developing effective solutions for LOC, and form the basis for developing test scenarios that can be used in evaluating them. Preliminary findings based on the results of this paper indicate that system failures or malfunctions, crew actions or inactions, vehicle impairment conditions, and vehicle upsets contributed the most to accidents and fatalities, followed by inclement weather or atmospheric disturbances and poor visibility. Follow-on research will include finalizing the analysis through a team consensus process, defining future risks, and developing a comprehensive set of test scenarios with correlation to the accidents, incidents, and future risks. Since enhanced engineering simulations are required for batch and piloted evaluations under realistic LOC precursor conditions, these test scenarios can also serve as a high-level requirement for defining the engineering simulation enhancements needed for generating them.

Journal of KONES. Powertrain and Transport, 2016

Lost of Control in Flight (LOC-I) is ordinarily associated with flight outside of the normal flight envelope, with nonlinear behaviours, and with an inability of the pilot to control the aircraft. These results provide a means for analysing accident data to establish whether or not the accident should be classified as LOC-I. Moreover, they help identify when the initial upset occurred, and when control was lost. The analysis also suggests which variables were involved, thereby providing clues as to the underlying mechanism of upset. However, it does not provide direct links to the flight mechanics of the aircraft, so it cannot be used proactively to identify weaknesses or limitations in the aircraft or its control systems. Moreover, it does not explain how departures from controlled flight occur. The complexity of the disaster aetiology stems from both the scale and coupling of the systems (not only the physical aircraft systems but also the organizational systems that support the operation). This complexity creates a pattern of disaster that evolves or it is precipitated through a series of several small failures. The cusp catastrophe model facilitates the mapping of Reason's latent failure model, providing a descriptive and predictive illustration of the emergence of latent conditions under the trigger of situational factors. The risk of an accident increases as the situational and systematic factors combine to create an inherent instability resulting in the catastrophic event

AIAA Guidance, Navigation, and Control Conference, 2010

Journal of Advanced Transportation, 2018

A rapid increase in the occurrence of loss of control in general aviation has raised concern in recent years. Loss of control (LOC) pertains to unique characteristics in which external and internal events act in conjunction. The Federal Aviation Administration (FAA) has approved an Integrated Safety Assessment Model (ISAM) for evaluating safety in the National Airspace System (NAS). ISAM consists of an event sequence diagram (ESD) with fault trees containing numerous parameters, which is recognized as casual risk model. In this paper, we outline an integrated risk assessment framework to model maneuvering through cross-examining external and internal events. The maneuvering is in the critical flight phase with a high number of LOC occurrences in general aviation, where highly trained and qualified pilots failed to maintain aircraft control irrespective of the preventive nature of the events. Various metrics have been presented for evaluating the significance of these parameters to i...

Loss-of-control remains a major type of mishap to transport airplanes. These have included several high-profile accidents worldwide which emphasize the need to prevent and recover from loss-of-control incidents. I reviewed loss-of-control events to revenue air carrier flights occurring from 1981 through 2010. During this period, I identified 203 events resulting in 8476 fatalities. Aerodynamic stalls (48 events; 1505 fatalities) was the most frequent cause. Spatial disorientation produced the second greatest number of fatalities (27 events; 1463 fatalities). Twenty events involved faulty recovery techniques and resulted in 1557 fatalities. The level of pilot experience was examined, but does not appear to be a significant factor. Three areas for improvements in pilot training were identified: Addressing loss of instrument skills; stall recovery training; and specific SDO training. Envelope protection appears to be the most significant airframe-related safety factor. I recommend developing retrofit envelope protection, new recovery displays, and changes to the ice-protection and takeoff warning requirements.

AIAA Guidance, Navigation, and Control Conference, 2014

Flying near the edge of the safe operating envelope is an inherently unsafe proposition. Edge of the envelope here implies that small changes or disturbances in system state or system dynamics can take the system out of the safe envelope in a short time and could result in loss-of-control events. This study evaluated approaches to predicting loss-of-control safety margins as the aircraft gets closer to the edge of the safe operating envelope. The goal of the approach is to provide the pilot aural, visual, and tactile cues focused on maintaining the pilot's control action within predicted loss-of-control boundaries. Our predictive architecture combines quantitative loss-of-control boundaries, an adaptive prediction method to estimate in real-time Markov model parameters and associated stability margins, and a real-time data-based predictive control margins estimation algorithm. The combined architecture is applied to a nonlinear transport class aircraft. Evaluations of various feedback cues using both test and commercial pilots in the NASA Ames Vertical Motion-base Simulator (VMS) were conducted in the summer of 2013. The paper presents results of this evaluation focused on effectiveness of these approaches and the cues in preventing the pilots from entering a loss-of-control event.

2009

Aviation, 2021

Inflight loss of control (LOC-I) is a significant cause of General Aviation (GA) fixed-wing aircraft accidents. The United States National Transportation Safety Board’s database provides a rich source of accident data, but conventional analyses of the database yield limited insights to LOC-I. We investigate the causes of 5,726 LOC-I fixed‑wing GA aircraft accidents in the United States in 1999–2008 and 2009–2017 using a state-based modeling approach. The multi-year analysis helps discern changes in causation trends over the last two decades. Our analysis highlights LOC-I causes such as pilot actions and mechanical issues that were not discernible in previous research efforts. The logic rules in the state-based approach help infer missing information from the National Transportation Safety Board (NTSB) accident reports. We inferred that 4.84% (1999–2008) and 7.46% (2009–2017) of LOC-I accidents involved a preflight hazardous aircraft condition. We also inferred that 20.11% (1999–2008...

International Journal of Modelling and Simulation, 1993

A computer model to study the response of an aircraft to disturbances of control elements is presented. . The general nondimensional small disturbance equations of motion are obtained in the form of linearized first-order differential equations. The equations are wri tten in vector form, and are denoted as the state equation. The Ztransform is used to obtain the recursion relation, which is the solution of the state equation. The numerical model is used to provide an illustration for airplane response to various simulated control faults during maneuvering or straight flight. It is concluded from the study that disturbances of the three control elements tend to activate several aircraft stabili ty modes , some of which may be unstable. In addition, the fault configuration seems to have a clear effect on the aircraft response within the fault-time domain.