【導讀】究成果，均加以特別標注并在此表示致謝。與我一同工作的同志對。本論文所做的任何貢獻也已在論文中作了明確的說明并表示謝意。特授權中國民航大學可以將畢業(yè)設計?？s印或掃描等復制手段保存、匯編以供查閱和借閱。家有關部門或機構送交畢業(yè)設計（論文）的復印件和磁盤。隨著民航運輸的快速發(fā)展，機場的起降航班量也迅速增加。由于機場軟件和硬件設施的。不足，機場機坪的運行變得越來越繁忙擁擠。機坪運行風險性大大增加，機坪事故頻發(fā)。多航空事故的發(fā)生都和地面機坪運行保障有一定關系。整個航空運輸的安全有著十分重要的意義。文章主要論述了機坪的特點、機坪的運行過程和機坪事故的分類。使用事故樹分析法建。造成這些機坪事故的風險因素，包括管理上的疏忽、設備的影響、人為因素和。運用灰色關聯(lián)分析法，計算風險因素之間的關聯(lián)度并按照大小排序，確定出影響。針對主要風險因素制定相應的控制和預防措施，全面保障機坪的

　　

【正文】 業(yè)論文 18 notional surfaces above which obstacles, such as new buildings, cannot extend. However, these surfaces do not apply to mobile obstacles to the same degree。 aircraft can wait at a point where a building of equivalent size would not be permitted. [Gleave 2020] Our risk assessment must consider not only the risk to landing aircraft due to those on the ground, but also the relationship in the opposite direction. What is the risk to an aircraft at a holding point due to landing aircraft? One hazard is the impact of debris due to a landing accident. There is a model available in the public domain for deriving the probabilities of impact in such a situation. It is an empirical model developed by National Air Traffic Services Limited from publicly available accident data. It is documented in a report [NATS 1996] that was publicised in support of a 1997 Consultation Document of the UK Government?s Department of the Environment, Transport and the Regions concerning Public Safety Zones around airports. The model provides equations with which to determine either the impact or wreckage location of an aircraft following an accident. Several equations are described which cater for all permutations of: Aircraft operation (approach or departure)。 Crash from flight, or runway run off, and, Crash location (before or after the prepared runway surface). These equations form a set of probability distribution functions of a crash occurring per unit probability of an aircraft being struck by debris due to a landing accident has four ponents,which are listed below. The product of these ponents gives the desired result. p(Accident) This figure represents the proportion of aircraft within the airport vicinity that have an incident that causes it to crash, or runoff the runway. p(Accident Type) This figure represents the type of accident the aircraft will have ( short of runway on approach, or run off the side of the runway). p(Risk Area) This figure represents the region that will be affected by the resulting crash or runoff. p(Aircraft) This figure represents the probability of an aircraft being in the Risk Area when accident occurs. These four probabilities are derived from several sources. The Accident Probability, p(Accident), is set by the assessor based on data provided by the airport. A pessimistic example for this figure is taken o be one accident per million operations, . p(Accident) = 1 10 worldwide average is quote as million departures per accident (of which about seventy percent are controlled flight into terrain), and in Europe, the rate is better 附錄 A 外文翻譯資料 19 than this. Figures from the Flight Safety Foundation [FSF1999] give the fatalaccident rate involving Western built large jets in the fullmember states of the European Joint Aviation Authorities (JAA) as over six million departures per fatal accident. We are interested in the nonfatal accidents too。 the total European figure is of the order of two million departures per accident. The Aircraft Probability, p(Aircraft), is also set by the assessor. It is dependent upon the airport environment, its operations and procedures. This parameter is the probability that an aircraft will be within the Risk Area at the time of an accident, and is prised of a number of factors. It takes into account the time a single aircraft will spend in the Risk Area, the number of aircraft moving through the Risk Area and a Proportion of Risk Area factor. The factor for Proportion of Risk Area is last is an artefact of the model, which requires a rectangular Risk Area to be specified. In practice the actual area of interest may not be rectangular, for example, consider a stretch of taxiway with a corner in it as shown in Figure 2. If the taxiway area of interest were between points ?A? and ?B?, the Risk Area would have to be specified as shown. However, an aircraft cannot occupy a large section of the Risk Area (in normal circumstances), so Proportion of Risk Area provides a means to adjust the p(Aircraft) value to more accurately reflect the probability of an aircraft in the Risk Are. Accident Type Probability and Risk Area Probability are independent of the airport under of these figures are taken from the crash location model equations. The Accident Type probabilities are fixed, set by the model ponents used. There are seven equations in the model that provide probability distributions for wreckage location following an accident in different scenarios. These equations are scaled in terms of probability per unit area. The Risk Area probability is determined by integrating the appropriate equations over the desired Risk Area limits. We do not actually use the model to provide absolute numbers。 rather it is used for parisons of options. For example, we can ask questions like: “what if this holding point is moved back fifty metres, how does it affect the probability?” The model has been used “manually” calculating particular cases。 but this gets very tedious and, hence, error prone if many options are tried. It was therefore also implemented in spreadsheet format, reducing the tedium to a data entry task. The spreadsheet functions were validated by parison with the hand calculations. More recently it has been implemented in a more flexible program using a windows based user interface. This also produces graphical output of results that can be overlaid on 中國民航大學本科畢業(yè)論文 20 a model of the airport geometry that has been previously input via the keyboard, from CAD plans, or even as aerial photographs. The graphical output helps in the presentation of the options to nontechnical stakeholders, such as the airport?s senior management, so that they can make their decisions based on a visualisation of the scenario rather than “meaningless” raw numbers. Care must be taken in the use of