Risk-based Modeling to Develop Zoning Criteria for Land-use Near Canadian Airports

Land development in the vicinity of airports often leads to land-use that can attract birds that are hazardous to aviation operations. For this reason, certain forms of land-use have traditionally been discouraged within prescribed distances of Canadian airports. However, this often leads to an unrealistic prohibition of land-use in the vicinity of airports located in urban settings. Furthermore, it is often unclear that the desired safety goals have been achieved. This paper describes a model that was created to assist in the development of zoning regulations for a future airport site in Canada. The framework links land-use to bird-related safety-risks and aircraft operations by categorizing the predictable relationships between: (i) different land uses found in urbanized and urbanizing settings near airports; (ii) bird species; and (iii) the different safety-risks to aircraft during various phases of flight. The latter is assessed relative to the runway approach and departure paths. Bird species are ranked to reflect the potential severity of an impact with an aircraft (using bird weight, flocking characteristics, and flight behaviours). These criteria are then employed to chart bird-related safety-risks relative to runway reference points. Each form of land-use is categorized to reflect the degree to which it attracts hazardous bird species. From this information, hazard and risk matrices have been developed and applied to the future airport setting, thereby providing risk-based guidance on appropriate land-uses that range from prohibited to acceptable. The framework has subsequently been applied to an existing Canadian airport, and is currently being adapted for national application. The framework provides a risk-based and science-based approach that offers municipalities and property owner’s flexibility in managing the risks to aviation related to their land use.

Modeling Age-Specific Mortality For Marine Mammal Populations

A method is presented for estimating age-specific mortality based on minimal information: a model life table and an estimate of longevity. This approach uses expected patterns of mammalian survivorship to define a general model of age-specific mortality rates. One such model life table is based on data for northern fur seals (Callorhinus ursinus) using Siler’s (1979) 5-parameter competing risk model. Alternative model life tables are based on historical data for human females and on a published model for Old World monkeys. Survival rates for a marine mammal species are then calculated by scaling these models by the longevity of that species. By using a realistic model (instead of assuming constant mortality), one can see more easily the real biological limits to population growth. The mortality estimation procedure is illustrated with examples of spotted dolphins (Stenella attenuata) and harbor porpoise (Phocoena phocoena).

A Model-Based Approach for Making Ecological Inference from Distance Sampling Data

We consider a fully model-based approach for the analysis of distance sampling data. Distance sampling has been widely used to estimate abundance (or density) of animals or plants in a spatially explicit study area. There is, however, no readily available method of making statistical inference on the relationships between abundance and environmental covariates. Spatial Poisson process likelihoods can be used to simultaneously estimate detection and intensity parameters by modeling distance sampling data as a thinned spatial point process. A model-based spatial approach to distance sampling data has three main benefits: it allows complex and opportunistic transect designs to be employed, it allows estimation of abundance in small subregions, and it provides a framework to assess the effects of habitat or experimental manipulation on density. We demonstrate the model-based methodology with a small simulation study and analysis of the Dubbo weed data set. In addition, a simple ad hoc method for handling overdispersion is also proposed. The simulation study showed that the model-based approach compared favorably to conventional distance sampling methods for abundance estimation. In addition, the overdispersion correction performed adequately when the number of transects was high. Analysis of the Dubbo data set indicated a transect effect on abundance via Akaike’s information criterion model selection. Further goodness-of-fit analysis, however, indicated some potential confounding of intensity with the detection function.

MATERIAL MODELING AND ANALYSIS FOR THE DEVELOPMENT OF A REALISTIC BLAST HEADFORM

Blast traumatic brain injury (BTBI) has become an important topic of study because of the increase of such incidents, especially due to the recent growth of improvised explosive devices (IEDs). This thesis discusses a project in which laboratory testing of BTBI was made possible by performing blast loading on experimental models simulating the human head. Three versions of experimental models were prepared – one having a simple geometry and the other two having geometry similar to a human head. For developing the head models, three important parts of the head were considered for material modeling and analysis – the skin, skull and brain. The materials simulating skin, skull and brain went through many testing procedures including dynamic mechanical analysis (DMA). For finding a suitable brain simulant, several materials were tested under low and high frequencies. Step response analysis, rheometry and DMA tests were performed on materials such as water based gels, oil based mixtures and silicone gels cured at different temperatures. The gelatins and silicone gels showed promising results toward their use as brain surrogate materials. Temperature degradation tests were performed on gelatins, indicating the fast degradation of gelatins at room temperature. Silicone gels were much more stable compared to the water based gels. Silicone gels were further processed using a thinner-type additive gel to bring the dynamic modulus values closer to those of human brain matter. The obtained values from DMA were compared to the values for human brain as found in literature. Then a silicone rubber brain mold was prepared to give the brain model accurate geometry. All the components were put together to make the entire head model. A steel mount was prepared to attach the head for testing at the end of the shock tube. Instrumentation was implemented in the head model to obtain effective results for understanding more about the possible mechanisms of BTBI. The final head model was named the Realistic Explosive Dummy Head or the “RED Head.” The RED Head offered potential for realistic experimental testing in blast loading conditions by virtue of its material properties and geometrical accuracy.