Johnathan_Council_Assignment 9.1

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1 Running head: BE-200 ACCIDENT ANALYSIS BE-200 Accident Analysis Johnathan Council Embry-Riddle Worldwide 13 March 2022

2 BE-200 ACCIDENT ANALYSIS Table of Content 1. Abstract………………………………………………………………………………………………………………3 2. Introduction………………………………………………………………………………………………………...4 3. Literature Review………………………………………………………………………………………………...4 4. Research Methods……………………………………………………………………………...………………...6 5. Results………………………………………………………………………………………………………………...8 6. Conclusions……………………………………………………….……………………………………………….10 7. Appendices……………………………………………………………………….……………………………….11 8. References………………………………………………………………………………………………………...13

3 BE-200 ACCIDENT ANALYSIS Abstract The United States is home to the largest and most diverse community of General Aviation (GA) aircraft and pilots in the world with over 200,000 aircraft in use (FAA, 2018). GA is comprised of a multitude of operations and various types of aircraft that range widely in complexity. These operations include flight instruction, tours, charters, surveying, and much more. Although GA operations have been in decline over the last few decades, they still account for over 25 million flight hours every year (FAA, 2021). The accident rate over the last decade in GA has been in decline as well with 2019 experiencing a rate of 4.88 per 100,000 flight hours with fatal accidents less 1.0 for every 100,000 flight hours (AOPA, n.d.). This diverse environment can make the endeavor of addressing safety concerns challenging for organizations such as the Federal Aviation Administration (FAA), the National Transport Safety Board (NTSB), and private owners and operators. This paper seeks to explore if there are phases of flight where accidents are more likely to occur in the BE-200 aircraft and if operations in complex aircraft such as this vary from the GA community. Such insight may determine the necessity for a more pointed approach during times when the FAA develops and implements rules and regulations aimed at addressing the accident rate in GA. This paper takes a historical look at all BE-200 accidents in the NTSB database and utilizes a Chi-Square Goodness-of-Fit test to determine if there is any significant difference in accidents and the phase of flight they occur in.

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4 BE-200 ACCIDENT ANALYSIS RSCH 665 BE-200 Accident Analysis Introduction A cursory review of the Annual Summary of US Civil Aviation Accidents data for 2019 by the NTSB indicates that out of nearly 2000 total accidents, the most likely phase of flight for a GA aircraft to experience an accident is during the landing phase (NTSB, 2020). Over the last 38 years, the NTSB CAROL database reported only 104 accidents involving the Beech 200 Super King Air (BE-200), of which nearly 90% were being operated under GA rules and regulations. While this BE-200 population is small in comparison to the entire GA population, it does represent the BE-200 accident population in its’ entirety and therefore should provide relative insight into the nature of accidents involving this specific type of aircraft. The data was collected by the researcher by examining all 104 NTSB accident reports between 1982 and 2020 and categorizing them type of operation, phase of flight during which the accident occurred, and cause of the accident. A taxonomy like the NTSB and Boeing annual accident reports was used for categorization. This research paper will examine whether there is a phase of flight where accidents are more prevalent and the relationship between BE-200s and GA accidents. Literature Review The NTSB Case Analysis and Reporting Online (CAROL) database was instrumental in gathering all the data for this research that concerned the BE-200. While the database alone does provide specific insight into trends, it does allow users to access all accident reports dating back to 1982. In addition to accident reports, the database allows users to access all the NTSBs safety reports. It is much more user friendly then the previous search engines and databases and provides users with a single point of reference.

5 BE-200 ACCIDENT ANALYSIS Every year, the NTSB issues an Annual Summary of US Civil Aviation Accidents Statistics. This data set allows readers and researchers to access and view large swaths of aviation accident data broken down between Part 121, Part 135, and GA operations. The data is further broken down into subcategories based on a multitude of variables. These reports were instrumental in that they provided a baseline to compare the BE-200 accident data. The only shortcoming is that the data is already processed and there is no access to the raw data making it challenging to conduct certain statistical tests. Boyd (2019) in his research exploring occupant injury involving excessive landing speeds discussed the frequency of accidents during landing sequences and how they influenced injury. Specifically, Boyd looked at the different conditions that resulted in accidents during landing such as slow speeds or landings outside the touchdown zone and how the different conditions related to injuries sustained by the passengers. In his research, he discussed how 30% of accidents in GA in 2014 were during the landing phase. He also discussed the fact that countries such as German had an even higher rate of accident during landing (53%). That being said, German GA does differ from U.S. GA in many ways. This research was useful in that it verified data from a different year group that would affirm the conclusion of my research. Boyd, Scharf, and Cross (2021) in their recent research looked at the landing data of GA accidents and the comparison pilots with various levels of FAA certificates (i.e., private, commercial, airline transport pilot (ATP) certificates). These various certificates can be representative of a certain degree of pilot experience but not always. In their research, they discovered that professional airline pilots were more apt to neglect FAA rules regarding approach procedures and weather briefs. In addition to that, they discuss the tighter tolerances for obtaining higher levels of certification. This article was useful in identifying the differences and

6 BE-200 ACCIDENT ANALYSIS deficiencies between various levels of certification which is something that this research would have considered had there been a larger population to draw data from. The research also reaffirmed that landings where the prevalent phase of flight where accidents occurred (27-39% depending on the group). An important distinction that was made was the leading causes of accidents during landing which varied dependent upon the level of certification. Knecht (2015) did in-depth research into the total flight hours (TFH) that pilots had in GA when the accident occurred. While this article does not directly pertain to the content of this research article, it did influence the direction that it went. The initial intent was to examine the TFH of BE-200 accident pilots, but as this article pointed out, the key to properly portraying the significance of TFH was to have the accident rate as well. Once this was realized, it became quickly apparent that ascertaining the accident rate of just the BE-200 aircraft would be difficult given the lack of information available. Research Methods In order to thoroughly investigate the accident history of the BE-200 aircraft, every accident report available in the NTSBs CAROL database was read. Of the 104 finalized reports listed between 1982 and 2020, 91 aircraft were operated as GA aircraft. However, for the purposes of this research, all accidents were categorized appropriately and utilized given the already small size of the population. Of the 104 accidents, enough information in the reports was available to categorize every accident in one of eight phases of flight where the occurred. These categories are climb, cruise, descent, final, landing, ramp, takeoff, and taxi. For the purposes of this research, any accident that occurred before the landing gear on takeoff was retracted were considered to be in the “climb” phase while the “landing” phase included any aircraft accidents that occurred beyond the threshold of the runway. The difference between “final” and “descent”

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7 BE-200 ACCIDENT ANALYSIS was whether the aircraft was established inside the initial approach fix for the approach to be flown or within the terminal area (i.e., within 12 miles of the airport). Because the research is examining categories (nominal), the Chi-Square Goodness-of-Fit test was used. This test was also used for the additional test of the 2019 GA accident data provided by the NTSB annual summary that a comparison could be drawn between the two populations. Table 1 shows the frequency of occurrence for accidents involving the BE-200 aircraft. Table 1: Frequency table results for BE-200 Flight Phase Accidents: Flight Phase Frequency Percent of Total Climb 12 11.54 Cruise 13 12.5 Descent 6 5.77 Final 22 21.15 Landing 37 35.58 Ramp 5 4.81 Takeoff 5 4.81 Taxi 4 3.84 TOTAL 104 100% Table 2 is a frequency chart for the accidents that occurred in GA and the phase of flight that they occurred in. This data was obtained from the NTSB annual summary report for 2019. Table 2: Frequency table results for 2019 GA Flight Phase Accidents: Flight Phase Frequency Percent of Total Climb 97 9.15 Cruise 200 18.87 Descent 9 0.85 Final 122 11.51 Landing 412 38.87 Ramp 14 1.32 Takeoff 162 15.28 Taxi 44 4.15

8 BE-200 ACCIDENT ANALYSIS Flight Phase Frequency Percent of Total TOTAL 1060 100% The populations in the study were phases of flight in this study and phases of flight where accidents are more like to occur. The Null Hypothesis is that accidents will occur equally across all phases of flights and the Research Hypothesis is that there are phases of flight where accidents are more prone to occur. In other words, it was anticipated that accidents occur during different phases of flight more often than others. As a population, aircraft typically experience every phase of flight unless there is an interruption that causes a halt in operation such as an accident or emergency. Aircraft do spend a different amount of time exposed to various phases of flight but that was not taken into consideration for this study. As mentioned, the most appropriate test for this data is the Chi-Square Goodness-of-Fit test with seven degrees of freedom and a significance level of .05. Results The data collected in StatCrunch was evaluated using the Chi-Square Goodness-of-Fit test. For the BE-200 aircraft, 104 accidents were analyzed with a .05 level of significance. With seven degrees of freedom, the resulting cutoff score was 14.0671. It was determined that there is a phase of flight that is significantly more prevalent in BE-200 accidents. Table 3 shows the results of the test from StatCrunch. Table 3: Chi-Square goodness-of-fit results: Observed: BE-200 Expected: All cells in equal proportion N DF Chi-Square P-value 104 7 70.461538 <0.0001

9 BE-200 ACCIDENT ANALYSIS Observed Expected 12 13 13 13 6 13 22 13 37 13 5 13 5 13 4 13 Because the population of the BE-200 database had such a small power (.53), data from the NTSB 2019 GA summary was analyzed as well to determine was any significant results that may speak to the significance of the BE-200 results. Using the same type of test, level of confidence, and cutoff score, it was determined that there was a phase of flight where aircraft experience a higher rate of accident that was similar to what was seen in the BE-200 test. The results are shown in Table 4. Table 4: Chi-Square goodness-of-fit results: Observed: 2019 GA Expected: All cells in equal proportion N DF Chi-Square P-value 1060 7 921.08679 <0.0001 Observed Expected 97 132.5 200 132.5 9 132.5 122 132.5 412 132.5 14 132.5 162 132.5 44 132.5

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10 BE-200 ACCIDENT ANALYSIS Conclusions Each test yielded a Chi-Square score well above the cutoff score of 14.0671 and both have low P-value indicating the significance of the observation. Because of this, the null hypothesis is rejected. The Chi-Square Good-of-Fit test results clearly demonstrate that most accidents within the BE-200 population occur during that landing phase. Similarly, the test results for the 2019 GA accident data also indicate that most accidents occur during the landing phase and because of the higher power (100), this supports the rejection of the null hypothesis. Given that BE-200s operate primarily as GA aircraft, the similar results were expected, and the supporting literature suggested that these results should be anticipated. The uniqueness of this test though was to demonstrate that regardless of aircraft complexity, as far as GA is concerned, there are many similarities in accident occurrences meaning that not all FAA rules and regulations should be pointed to specific aircraft types. There were measurable differences between the second and third phases of flight where accidents occurred which may mean that for this BE-200 aircraft, maybe there is specific guidance or training that can be implemented by owner/operators and the FAA to address aircraft specific concerns. At a minimum, this should indicate the necessity for more aircraft specific research if the FAA intends to continue fighting to reduce the accident rate in GA. Such research could result in the means to develop specific approaches for addressing the various concerns addressing a wide range of aircraft and operations. Appendices Tables

11 BE-200 ACCIDENT ANALYSIS Table 1: Frequency table results for BE-200 Flight Phase Accidents: Flight Phase Frequency Percent of Total Climb 12 11.54 Cruise 13 12.5 Descent 6 5.77 Final 22 21.15 Landing 37 35.58 Ramp 5 4.81 Takeoff 5 4.81 Taxi 4 3.84 TOTAL 104 100% Table 2: Frequency table results for 2019 GA Flight Phase Accidents: Flight Phase Frequency Percent of Total Climb 97 9.15 Cruise 200 18.87 Descent 9 0.85 Final 122 11.51 Landing 412 38.87 Ramp 14 1.32 Takeoff 162 15.28 Taxi 44 4.15 TOTAL 1060 100% Table 3: Chi-Square goodness-of-fit results: Observed: BE-200 Expected: All cells in equal proportion N DF Chi-Square P-value 104 7 70.461538 <0.0001 Observed Expected 12 13 13 13 6 13 22 13 37 13 5 13 5 13

12 BE-200 ACCIDENT ANALYSIS Observed Expected 4 13 Table 4: Chi-Square goodness-of-fit results: Observed: 2019 GA Expected: All cells in equal proportion N DF Chi-Square P-value 1060 7 921.08679 <0.0001 Observed Expected 97 132.5 200 132.5 9 132.5 122 132.5 412 132.5 14 132.5 162 132.5 44 132.5 References

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13 BE-200 ACCIDENT ANALYSIS AOPA. (2020, July 21). The 31st Joseph T. Nall Report . AOPA. Retrieved March 13, 2022, from https://www.aopa.org/training-and-safety/air-safety-institute/accident-analysis/joseph-t- nall-report/nall-report-figure-view?category=all&year=2019&condition=all&report=true Aron, A., Coups, E. J., & Aron, E. (2019). Statistics for the behavioral and Social Sciences: A brief course . Pearson. Boyd, D. D. (2019). Occupant injury severity in general aviation accidents involving excessive landing airspeed. Aerospace Medicine and Human Performance , 90 (4), 355–361. https://doi.org/10.3357/amhp.5249.2019 Boyd, D. D., Scharf, M., & Cross, D. (2021). A comparison of general aviation accidents involving airline pilots and instrument-rated private pilots. Journal of Safety Research , 76 , 127–134. https://doi.org/10.1016/j.jsr.2020.11.009 FAA. (2018, July 30). General Aviation Safety . General Aviation Safety | Federal Aviation Administration. Retrieved March 13, 2022, from https://www.faa.gov/newsroom/general- aviation-safety FAA. (2021, November 2). Air Traffic by the Numbers . Air traffic by the numbers. Retrieved March 13, 2022, from https://www.faa.gov/air_traffic/by_the_numbers/ Knecht, W. R. (2015). The “killing zone” revisited: Serial nonlinearities predict general aviation accident rates from pilot total flight hours. Accident Analysis & Prevention , 60 , 50–56. https://doi.org/10.1016/j.aap.2013.08.012 NTSB. (n.d.). Annual Summary of the US Civil Aviation Accidents 2019 . Annual Summary of US Civil Aviation accidents. Retrieved March 13, 2022, from https://www.ntsb.gov/safety/data/Pages/AviationDataStats2019.aspx# NTSB. (n.d.). CAROL Database . Page not found. Retrieved March 13, 2022, from https://data.ntsb.gov/carol-main-public/basic-search