Abstract
The current study investigates the application of statistical methods to flight, which have been used in science over time to understand complex physical and mathematical systems by using randomly generated numbers as input into those systems to generate a range of solutions and, specifically, how mathematics is used to examine airplane design and crash frequency. In order to make very accurate predictions, one also requires an appropriate mathematical model. Using randomly selected numbers, the Monte Carlo statistical method is able to make very accurate predictions. With the Monte Carlo statistical method, by using significantly larger numbers of trials, the likelihood of the solutions can be determined very accurately. Currently, Monte Carlo methods are widely used and play a key part in various fields of science. Monte Carlo methods have vast uses in trials with limited observations that cannot be replicated many times. This paper adds new findings to the knowledge base on causes of crashes by airplane design. First, mathematical methods are used in this paper to investigate what the most likely casualty number and range are in the five years after the first flight based on 5000 simulations. Second, an investigation is performed to determine if certain casualty numbers are outliers of certain airplane designs based on the number of casualties reported using Monte Carlo analysis.
Highlights
Monte Carlo methods were invented in the 1930s by Enrico Fermi [1,2] and were used to solve crucial problems in developing the atomic bomb in the 1940s
This paper looks at some applications in flight that have been used over time and how mathematics is used to examine airplane design and crash frequency [9]
Mathematical methods are used in this paper to investigate what the most likely casualty number and range are in the five years after the first flight based on 5000 simulations
Summary
Monte Carlo methods were invented in the 1930s by Enrico Fermi [1,2] and were used to solve crucial problems in developing the atomic bomb in the 1940s. Fermi took great delight in impressing greatly his Roman colleagues with his remarkably accurate, “too-good-to-believe” predictions of experimental results. After indulging himself, he revealed that his “guesses” were really derived from Monte Carlo statistical sampling techniques. He revealed that his “guesses” were really derived from Monte Carlo statistical sampling techniques Fermi, during his hiatus from the ENIAC operation at Los Alamos National Laboratory, invented a simple but ingenious analog device for studies in neutron transport collision, and he persuaded his friend and collaborator Percy King to build such an instrument, later called the FERMIAC. Modern computer architecture provides a solution for this problem with the linear increase of computing performance as computing cores in the silicon microchip increase
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
