Improved Models for Risk Assessment of Runway Safety Areas (2011)

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28 Overview One of the main project goals was to develop an analysis tool to incorporate the approach and the models developed in this study. The software is called Runway Safety Area Risk Analysis (RSARA). The program and the accompanying user’s guide are available on the accompany CD with this report. In addition, the user’s guide is available in Appendix I. RSARA is a Windows-based system developed to facilitate characterizing analysis conditions and entering required data. The software main screen is shown in Figure 36. Software Capabilities RSARA was tailored to help airport stakeholders evaluate different RSA alternatives. The software has the following capabilities: • Performs full risk assessment for multiple runways. • Enters multiple obstacles to each RSA scenario. • Characterizes different categories for obstacles. • Defines and analyzes non-standard (non-rectangular) RSA geometry. • Analyzes with standard and non-standard EMAS beds. • Internally integrates operations and weather data from separate files. • Automatically converts operations and weather data into parameters used by probability models. • Includes database of aircraft with capability to add new or edit existing aircraft. • Automatically computes runway criticality factor for each operation. • Automatically corrects for required distances (landing and takeoff) based on elevation, temperature, wind, and runway surface condition. • Generates analysis reports from software with summaries of following parameters: – Average risk for each type of incident by runway, by RSA section, and total for the airport. – The expected number of years to occur an accident for a user-defined annual traffic volume and growth rate. – Percentage of operations subject to a probability higher than a user-defined target level of safety (TLS). – Graphical outputs with the distribution of risk for each RSA and each type of event. Input Data Input data required to run the analysis include the follow- ing information: • Sample of historical operations data (date and time, aircraft model, runway used, type of operation, etc.). • Sample of historical weather data for the airport covering the period of sample of historical operations (wind, tem- perature, precipitation, visibility, etc.). • Characteristics of runways (elevation, direction, declared distances). • Characteristics of RSAs (geometry, type of surface, pres- ence of EMAS, location, size and category of obstacles). • General information (airport annual traffic volume, annual growth rate). Much of the input information is arranged in table format. Operations and weather data are entered using Microsoft Excel templates with automatic checks for value ranges and data format. Figure 37 shows the program screen and template to input operations data. The template for drawing the RSA area for overrun and un- dershoot was created using Microsoft Excel. It consists of a can- vas area formed by a matrix of cells. Each cell corresponds to a coordinate that is referenced to the center of the runway. The default coordinate grid is set at 10 × 10 ft. If the RSA is larger than the available canvas, a new scale can be set at the top of the C H A P T E R 5 Analysis Software

29 Figure 36. RSARA—main program screen. Figure 37. Example of input screen and template.

Each folder contains the risk estimates for each type of incident and individual operation and the total risk during landings and takeoffs. The results for each individual runway are provided in separate output Excel files. The summary table provides the average risk for each type of accident and expected number of years for an accident to occur. The accu- mulated risk distribution is provided in graphical form for each section of the RSA. The results for the entire airport are provided in one output Excel file. The user must create the output files for each runway prior to creating the output file for the airport. An example pre- senting the summary of results for the whole airport is shown in Figure 39. The main table contains a summary of average risk levels for each type of incident and for all incidents. Risk levels are shown in terms of accident rates per number of operations and expected number of years to occur one accident. Additional 30 canvas template. The user assigns a letter or number to each cell to define the type of surface or category of obstacle. After enter- ing a code, the color of the cell will change according to the sur- face type or obstacle entered to facilitate the visualization of the drawing. Tables with the codes describing the surface types and obstacles available are provided in the template. Figure 38 shows an example of RSA defined with the tool. Output and Interpretation When the analyses are completed, the user may see the results using the Output option of the main menu. There are two types of results: runways or the consolidated results for the whole airport. Within each of these options, the user can view the results for risk of events taking place outside the RSA or view the analysis output for the risk of accidents. Figure 38. RSA characterization using Microsoft Excel.

tables are presented showing the average risk for each RSA sec- tion, the percentage of movements with higher risk, and the number of operations challenging each RSA section. The first table contains three user-defined fields: the air- port annual traffic volume, the expected annual traffic growth rate, and the TLS. These values reflect the options entered during the analysis input phase and may be modified by the user directly in the output spreadsheet. When these parame- ters are changed, the average number of years between inci- dents will change to reflect the new traffic volume estimated for future years. If the TLS is modified, the percentage of move- ments above the TLS will change automatically to reflect the new TLS value. Software Field Test Appendix G provides details of the plan to field test RSARA. The plan involved testing by eight volunteers from FAA staff, airport operators, university professors, industry representa- tives, and consultants. The volunteers received the installa- tion software with the user’s guide to perform analysis and recommend changes. A questionnaire was prepared to gather comments from the volunteers, and their notes were used to improve the beta ver- sion of the software. During the trial period, the research team provided technical support by answering questions, solving installation problems, and fixing bugs. 31 Figure 39. Example output summary.