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This paper outlines a comprehensive, structured, and robust methodology for decision making in the early phases ofaircraft design. The proposed approach is referred to as the Technology Identification, Evaluation, and Selection (TIES) method. The seven-step process provides the decision maker/designer with an ability to easily assess and trade-off the impact of various technologies in the absence of sophisticated, time-consuming mathematical formulations. The method also provides a framework where technically feasible alternatives can be identified with accuracy and speed. This goal is achieved through the use of various probabilistic methods, such as Response Surface Methodology and Monte Carlo Simulations. Furthermore, structured and systematic techniques are utilized to identify possible concepts and evaluation criteria by which comparisons could be made.

Cutter runout has been a target for monitoring and control of machining processes in view of the constraint it places on the achievable productivity. Off-line metrology based on various displacement probes such as dial indicators or proximity sensors provides information regarding the runout characteristics in a non-cutting state. However, during the actual process of machining off-line calibrations often become irrelevant since the cutting parameters and machining configuration significantly affect the behavior of runout. This paper presents a methodology of in-process identification of cutter runout in end milling based on the analysis of cutting forces. The presence of cutter runout generates cutting force components at one spindle frequency above and below the tooth passing frequency.

The design of hypersonic vehicles is influenced by tightly coupled interactions between aerodynamics, propulsion, and structures. Therefore, in the conceptual design phases, the identification and mitigation of potential problem areas and disciplinary interrelations are critical. Although the multidisciplinary character of hypersonic designs is well known, research in hypersonics is primarily focused on the isolated disciplines with side notes on the interactions. The designer has to integrate all the disciplinary information and create a successful system. This integration is a tedious and elaborate process involving time-consuming iterations. This paper proposes a new approach and entails the creation of Response Surface Equations from the various constituent disciplines considered. This method allows to quickly assess the implication of design decisions at the top level using the multiple disciplinary meta-models.

The ultimate goal of knowledge-based aircraft design, pilot training and flight operations is to make flight safety an inherent, built-in feature of the flight vehicle, such as its aerodynamics, strength, economics and comfort are. Individual flight accidents and incidents may vary in terms of quantitative characteristics, circumstances, and other external details. However, their cause-and-effect patterns often reveal invariant structure or essential causal chains which may re-occur in the future for the same or other vehicle types. The identification of invariant logical patterns from flight accident reports, time-histories and other data sources is very important for enhancing flight safety at the level of the ‘pilot - vehicle -operational conditions’ system. The objective of this research project was to develop and assess a method for ‘mining’ knowledge of typical cause-and-effect patterns from flight accidents and incidents.