Building the safety case for UAS operations in support of natural disaster response

A framework supporting the systematic development of safety cases for Unmanned Aircraft System (UAS) operations in a broad range of civil and commercial applications is presented. The case study application is the use of UAS for disaster response. In those States where regulations do not preclude UAS operations altogether, approvals for UAS operations can be granted on a case-by-case basis contingent on the provision of a safety case acceptable to the relevant National Airworthiness Authority (NAA). A safety case for UAS operations must show how the risks associated with the hazards have been managed to an acceptable level. The foundational components necessary for structuring and assessing these safety cases have not yet been proposed. Barrier-bow-tie models are used in this paper to structure the safety case for the two primary hazards of 1) a ground impact, and 2) a Mid-Air Collision (MAC). The models establish the set of Risk Control Variables (RCVs) available to reduce the risk. For the ground-impact risk model, seven RCVs are identified which in combination govern the probability of an accident. Similarly, ten RCVs are identified within the MAC model. The effectiveness of the RCVs and how they can implemented in terms of processes, policies, devices, practices, or other actions for each of the case-study applications are discussed. The framework presented can provide for the more systematic and consistent regulation of UAS through a "safety target" approach.

Causal factors of hot air ballooning incidents : identification, frequency, and potential impact

Background: Hot air ballooning incidents are relatively rare, however, when they do occur they are likely to result in a fatality or serious injury. Human error is commonly attributed as the cause of hot air ballooning incidents; however, error in itself is not an explanation for safety failures. This research aims to identify, and establish the relative importance of factors contributing towards hot air ballooning incidents. Methods: Twenty-two Australian Ballooning Federation (ABF) incident reports were thematically coded using a bottom up approach to identify causal factors. Subsequently, 69 balloonists (mean 19.51 years’ experience) participated in a survey to identify additional causal factors and rate (out of seven) the perceived frequency and potential impact to ballooning operations of each of the previously identified causal factors. Perceived associated risk was calculated by multiplying mean perceived frequency and impact ratings. Results: Incident report coding identified 54 causal factors within nine higher level areas: Attributes, Crew resource management, Equipment, Errors, Instructors, Organisational, Physical Environment, Regulatory body and Violations. Overall, ‘weather’, ‘inexperience’ and ‘poor/inappropriate decisions’ were rated as having greatest perceived associated risk. Discussion: Although errors were nominated as a prominent cause of hot air ballooning incidents, physical environment and personal attributes are also particularly important for safe hot air ballooning operations. In identifying a range of causal factors the areas of weakness surrounding ballooning operations have been defined; it is hoped that targeted safety and training strategies can now be put into place removing these contributing factors and reducing the chance of pilot error.

Simulation and modelling tools for quantitative safety assessments of unmanned aircraft systems and operations

This paper presents two simple simulation and modelling tools designed to aid in the safety assessment required for unmanned aircraft operations within unsegregated airspace. First, a fast pair-wise encounter generator is derived to simulate the See and Avoid environment. The utility of the encounter generator is demonstrated through the development of a hybrid database and a statistical performance evaluation of an autonomous See and Avoid decision and control strategy. Second, an unmanned aircraft mission generator is derived to help visualise the impact of multiple persistent unmanned operations on existing air traffic. The utility of the mission generator is demonstrated through an example analysis of a mixed airspace environment using real traffic data in Australia. These simulation and modelling approaches constitute a useful and extensible set of analysis tools, that can be leveraged to help explore some of the more fundamental and challenging problems facing civilian unmanned aircraft system integration.

Air pollution levels measured at traffic hot spots : Brisbane urban corridor study

Air pollution levels were monitored continuously over a period of 4 weeks at four sampling sites along a busy urban corridor in Brisbane. The selected sites were representative of industrial and residential types of urban environment affected by vehicular traffic emissions. The concentration levels of submicrometer particle number, PM2.5, PM10, CO, and NOx were measured 5-10 meters from the road. Meteorological parameters and traffic flow rates were also monitored. The data were analysed in terms of the relationship between monitored pollutants and existing ambient air quality standards. The results indicate that the concentration levels of all pollutants exceeded the ambient air background levels, in certain cases by up to an order of magnitude. While the 24-hr average concentration levels did not exceed the standard, estimates for the annual averages were close to, or even higher than the annual standard levels.

Guidelines on building design and operation to minimize air quality impacts from major roads in transit oriented development

Poor air quality has a huge detrimental effect, both economic and on the quality of life, in Australia. Transit oriented design (TOD), which aims to minimise urban sprawl and lower dependency on vehicles, leads to an increasing number of buildings close to transport corridors. This project aims at providing guidelines that are appropriate to include within City Plan to inform future planning along road corridors, and provide recommendations on when mitigation measures should be utilised.

Implication of global warming on air-conditioned office buildings in Australia

With the accelerated trend of global warming, the thermal behavior of existing buildings, which were typically designed based on current weather data, may not be able to cope with the future climate. This paper quantifies, through computer simulations, the increased cooling loads imposed by potential global warming and probable indoor temperature increases due to possible undersized air-conditioning system. It is found from the sample office building examined that the existing buildings would generally be able to adapt to the increasing warmth of 2030 year Low and High scenarios projections and 2070 year Low scenario projection. However, for the 2070 year High scenario, the study indicates that the existing office buildings, in all capital cities except for Hobart, will suffer from overheating problems. When the annual average temperature increase exceeds 2°C, the risk of current office buildings subjected to overheating will be significantly increased. For existing buildings which are designed with current climate condition, it is shown that there is a nearly linear correlation between the increase of average external air temperature and the increase of building cooling load. For the new buildings, in which the possible global warming has been taken into account in the design, a 28-59% increase of cooling capacity under 2070 High scenario would be required to improve the building thermal comfort level to an acceptable standard.

Characterisation of indoor air organic pollutants in Brisbane

The occurrence and levels of airborne polycyclic aromatic hydrocarbons and volatile organic compounds in selected non-industrial environments in Brisbane have been investigated as part of an integrated indoor air quality assessment program. The most abundant and most frequently encountered compounds include, nonanal, decanal, texanol, phenol, 2-ethyl-1-hexanol, ethanal, naphthalene, 2,6-tert-butyl-4-methyl-phenol (BHT), salicylaldehyde, toluene, hexanal, benzaldehyde, styrene, ethyl benzene, o-, m- and pxylenes, benzene, n-butanol, 1,2-propandiol, and n-butylacetate. Many of the 64 compounds usually included in the European Collaborative Action method of TVOC analysis were below detection limits in the samples analysed. In order to extract maximum amount of information from the data collected, multivariate data projection methods have been employed. The implications of the information extracted on source identification and exposure control are discussed.