Mary S. Reveley

Predictive safety analytics: inferring aviation accident shaping factors and causation

This paper illustrates the development of an object-oriented Bayesian network (OOBN) to integrate the safety risks contributing to an in-flight loss-of-control aviation accident. With the creation of a probabilistic model, inferences about changes to the states of the accident shaping or causal factors can be drawn quantitatively. These predictive safety inferences derive from qualitative reasoning to conclusions based on data, assumptions, and/or premises, and enable an analyst to identify the most prominent causal factors leading to a risk factor prioritization. Such an approach facilitates a mitigation portfolio study and assessment. The model also facilitates the computation of sensitivity values based on perturbations to the estimates in the conditional probability tables. Such computations lead to identifying the most sensitive causal factors with respect to an accident probability. This approach may lead to vulnerability discovery of emerging causal factors for which mitigations do not yet exist that then informs possible future R&D efforts. To illustrate the benefits of an OOBN in a large and complex aviation accident model, the in-flight loss-of-control accident framework model is presented.

AN OVERVIEW OF THE NASA AVIATION SAFETY PROGRAM ASSESSMENT PROCESS

The objectives of the NASA Aviation Safety Program (AvSP) are (1) to develop and demonstrate technologies that reduce aircraft accident rate and (2) to develop technologies that reduce aviation injuries and fatalities when accidents do occur. The primary goal of Program Assessment is to examine the set of products in the AvSP portfolio to determine their projected impact on increasing aviation safety. This portfolio analysis is conducted using the following metrics: technical risk, implementation risk, fatal accident rate, safety benefits/cost and projected impact on safety risk. This paper provides an overview of the process that will be used for the final assessment of the NASA Aviation Safety Program.

A Preliminary Study on Systems Health Management and the Assessment of Future Research Requirements: A Safety Perspective

A health management (HM) system is responsible for information gathering about a system’s health and corresponding decision-making. HM systems are typically used to identify any degradation in performance that may affect safety or successful operations of a system. Effective long term development of successful health management solutions requires an improved understanding of the relationship between potential adverse events that may happen during flight, and validated tools, technologies, and techniques developed for mitigating their negative effects on system safety and functionality. This paper presents a study on the assessment of future requirements for systems health management technologies and related research areas. The gist of the paper is the mapping between systems health management technologies and damage conditions extracted from a study of aircraft accident and incident data. The goal of the study is to identify key research areas in systems health management and to recommend specific technology needs to support the development of integrated system health management tools, technologies, and techniques that will address safety related challenges facing current and future aircraft systems.Copyright