Experimental and Numerical Investigation of 65-deg Delta and 65/40-deg Double-Delta Wings

In this study, an experimental and numerical investigation was carried out to obtain lift, drag, and pitching moment data on 65-deg delta and 65/40-deg double-delta wings. The experimental tests were conducted at the KFUPM low-speed wind tunnel facility whereas the numerical tests were performed using the commercial CFD software FLUENT. Results from both experiments and numerical predictions were compared to other experimental data found in literature as well as to the theory of Polhamus. The results of comparison of surface pressure coefficient distribution and vortex breakdown location show good agreement with experiments. Overall the comparison of result shows good agreement between different experimental studies as well as good agreement with the CFD predictions and the theoretical calculation

Experimental and Numerical Investigation of 65-deg Delta and 65/40-deg Double-Delta Wings

In this study, an experimental and numerical investigation was carried out to obtain lift, drag, and pitching moment data on 65-deg delta and 65/40-deg double-delta wings. The experimental tests were conducted at the KFUPM low-speed wind tunnel facility whereas the numerical tests were performed using the commercial CFD software FLUENT. Results from both experiments and numerical predictions were compared to other experimental data found in literature as well as to the theory of Polhamus. The results of comparison of surface pressure coefficient distribution and vortex breakdown location show good agreement with experiments. Overall the comparison of result shows good agreement between different experimental studies as well as good agreement with the CFD predictions and the theoretical calculation

Failure Forecasting of Aircraft Air-Conditioning/Cooling Pack with Field Data

This paper presents methods for modeling the failure of air-conditioning/cooling packs for a particular type of aircraft with field data. In many regards, field data are highly desirable for more accurate failure prediction by aircraft operators, because the data implicitly account for all actual usage and environmental stresses. It is not always possible to accurately anticipate or simulate these stresses in a laboratory or even in a field test. Field data, in a larger extent, are also important to the manufacturer, because the data identify product deficiencies and areas of improvement. In this study, the failure of the aircraft air-conditioning/cooling pack under a customer-use environment is first modeled at the component level by using the Weibull distribution and its extensions. These include the two-parameter Weibull model, three-parameter Weibull model, mixture model, and phased bi-Weibull model. The number of failures over time is estimated by a renewal process. The failure of the air-conditioning/cooling pack at the system level is then modeled by using the power law process model. The failure trend is tested by the Laplace test. The results give an insight into the reliability and quality of the air-conditioning/cooling pack under actual operating conditions. The models presented here can be used by aircraft operators for assessing system and component failures and customizing the maintenance programs recommended by the manufacturer

Failure Data Analysis for Aircraft Maintenance Planning

This paper presents an application of Weibull method for forecasting the failure rate of Boeing 737 Auxiliary power unit (APU) oil pumps. The Weibull method is extremely useful for maintenance planning. Using Weibull failure forecasting, a maintenance planner can make quantitative trades between scheduled and unscheduled maintenance or non-destructive inspection and replacement. The method also helps for determining the age at which an operating part in an aircraft system should be replaced with a new part. In this study, the failure rate of APU oil pump of Boeing 737 aircraft is modeled by using the Weibull technique. The results were in close agreement with the real data indicating the validity of the Weibull model in predicting failure rate of failure for APU oil pumps. In addition, the optimum replacement age of the pumps is also calculated for various cost ratios