For many years, deceleration systems developed in an evolutionary fashion. This evolution needed flight test and experimental data. Concurrently, payload became much more expensive and needed to be safer. Today, there are a variety of methods employed to recover airborne bodies such as bio-capsules, reentry satellites, carrier missiles' boosters, reentry satellites, etc. Most of these methods make use of a parachute landing system in which recovery occurs in multiple phases. This paper studies the final phase of the subsonic recovery scenario for which a multi-phase deceleration system has been designed. To observe and evaluate system performance, a test projectile is designed that accelerates the payload to a certain velocity in order to test the recovery system. Finally, theoretical and test results are compared to indicate the appropriate design and reliable deceleration velocity in a space payload recovery.

Data mining is an iterative process in which progress is defined by discovery through either automatic or manual methods. A data cleaning procedure is proposed to improve the quality of classification tasks in the knowledge discovery process by taking into account both redundant and conflicting data. The redundancy check is performed on the original dataset and the resultant dataset is preserved. This resultant dataset is then checked for conflicting data and, if any are found, they are corrected and updated on the original aircraft dataset. This updated dataset is then classified using a variety of classifiers such as Bayes, functions, lazy, MISC, rules and decision trees. The performance of the updated datasets on these classifiers is examine, and the result shows a significant improvement in the classification accuracy after redundancy and conflicts are removed. The conflicts after correction are updated in the original dataset, and when the performance of the classifier is evaluated, great improvement is observed. This paper aims to address how data mining techniques can be used to understand complex system accidents in the aviation domain. Decision trees are considered to be the one of the most powerful and popular approaches in knowledge discovery and data mining. The objective is to develop a classification model for aviation risk investigation and reduction using a decision tree induction method that enhances the ability to form decision trees and thereby proves that the classification accuracy of decision trees is greater. Different feature selectors are used in this study in order to reduce the number of initial attributes.

This paper provides a set of closed form solutions for the lift and drag of wings flying in ground effect both with and without end plates. The developed theories are based on observations of several independent sources of controlled model tests over ground planes and over water and on previous theories prepared by researchers from the original work by Prandtl and Wieselsberger to the present day. The theories developed cover wings of varying aspect ratio, thickness to chord ratios and angle of attack. The results for wings with end plates include the effect of ground (or surface) clearance height, end plate depth and air gap depths beneath the wings or end plates. Good agreement is found between the developed theory and test.

Model-Order Reduction (MOR) is an important technique that allows Reduced-Order Models (ROMs) of physical systems to be generated that can capture the dominant dynamics, but at lower cost than the full order system. One approach to MOR that has been successfully implemented in fluid dynamics is the Eigensystem Realization Algorithm (ERA). This method requires only minimal changes to the inputs and outputs of a CFD code so that the linear responses of the system to unit impulses on each input channel can be extracted. One of the challenges with the method is to specify the size of the input pulse. An inappropriate size may cause a failure of the code to converge due to non-physical behaviour arising during the solution process. This paper addresses this issue by using piston theory to estimate the appropriate input pulse size.

Flight testing is both vital for collecting data for aeronautic research and at the same time fascinating for its contributors. Taking a glider as a versatile test bed example, this paper presents a transnational measurement campaign within the framework of a collaborative project funded by the European Commission. This project Advanced In-Flight Measurement Techniques 2 (AIM²) is a follow-up of Advanced In-Flight Measurement Techniques (AIM) and dedicated to developing and enhancing promising optical metrology for various flight test applications up to an industrial level.

The Image Pattern Correlation Technique (IPCT) and infrared thermography (IRT) are two of these modern non-intrusive measurement methods that were further developed and applied to the glider test bed within the scope of AIM². Focusing on optical deformation measurements with IPCT the experimental setup, the flight testing and results are summarily discussed. Gliders are not commonly used flight test platforms, which is why this contribution concludes with some lessons learned in general and especially related to the presented application. The experience to be shared with the flight testing community addresses equipment preparation, data collection and processing as well as how to meet official requirements and perform test flight operations in a dense controlled airspace.

The gas dynamic laser is numerically studied using quasi-1D and 2D simulations to investigate the effect of diamond pattern of the supersonic flow field (inhomogeneities in density field) on the laser's performance. The system of governing equations is solved with a finite volume approach using a structured grid in which the AUSM+ scheme is used to calculate the convective fluxes. Vibrational temperature of different modes, population inversion and the small signal gain are studied, and the effect of the divergent nozzle's geometry at the maximum gain is analysed.

Simultaneous modelling of aerodynamics, structure and flight dynamics is used to predict the gust loads on a model of 18-metre wingspan sailplane that includes bending flexibility. The ASWING software is used to analyse the time history of the wing-bending moment and the shear force at the wing root for the design gust speed and for the design maximum speed at different wavelengths of a ‘1-Cosine’ gust. Maximum values from the time history were compared with certification requirements for rigid sailplanes. The analysis revealed that wing-bending flexibility reduces the loads.