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The purpose of this paper is to present a formulation that couples equivalent plate and beam models for aircraft structures analysis, suitable in conceptual design in which fast model generation and efficient analysis capability are required.

Assembling the complete model with common techniques such as Lagrange multipliers or penalty function method would require a solver capable of handling the combined set of linear equation. The alternative approach proposed here is based on a static reduction of the beam model at specified connection points and the subsequent “embedding” into the equivalent plate model using a coordinate transformation, translating physical dfs in Ritz coordinates, i.e. polynomial coefficients. Displacements and forces on beam elements are recovered with the inverse transformation once the solution is computed.

An aeroelastic trim analysis on a Transonic CRuiser (TCR) civil aircraft conceptual model validates the hybrid model: as the TCR features a slender flexible fuselage and a wide root chord wing, the capability to reduce the beam model for the fuselage at more than one connection point improved aeroelastic corrections to steady longitudinal aerodynamic derivatives.

Although the equivalent model proposed is simpler than others found in literature, it offers automatic mesh generation capabilities, and it is fully integrated into an aeroelastic framework. The hybrid model represents an enhancement allowing both dynamical and static analyses.

The purpose of this paper is to document an efficient and accurate approach to generate aerodynamic tables using computational fluid dynamics. This is demonstrated in the context of a concept transport aircraft model.

Two designs of experiment algorithms in combination with surrogate modelling are investigated. An adaptive algorithm is compared to an industry-standard algorithm used as a benchmark. Numerical experiments are obtained solving the Reynolds-averaged Navier–Stokes equations on a large computational grid.

This study demonstrates that a surrogate model built upon an adaptive design of experiments strategy achieves a higher prediction capability than that built upon a traditional strategy. This is quantified in terms of the sum of the squared error between the surrogate model predictions and the computational fluid dynamics results. The error metric is reduced by about one order of magnitude compared to the traditional approach.

This work lays the ground to obtain more realistic aerodynamic predictions earlier in the aircraft design process at manageable costs, improving the design solution and reducing risks. This may be equally applied in the analysis of other complex and non-linear engineering phenomena.

This work explores the potential benefits of an adaptive design of experiment algorithm within a prototype working environment, whereby the maximum number of experiments is limited and a large parameter space is investigated.

The authors of this paper contend that too many firms' innovation initiatives are shackled with archaic budgeting and planning methodologies that are intended to protect managers from the embarrassment of blown budgets, missed deadlines, or market flops but instead suppress learning and adaptability, both critical to achieving successful commercialization of unique ideas. This paper aims to address this issue.

The authors propose that the first step to rid myopia and rigidity from the stage‐gate approach is to re‐conceive it as an assumption‐driven process centered on learning, rather than simply a sequence of activities marching towards a pre‐determined outcome.

The authors suggest that firms should adopt assumption‐driven learning in a series of sequential divergent‐convergent cycles – one cycle per stage – each centered on testing the major assumptions for that stage.

Continuous learning and unlearning is essential to the process of developing raw ideas into viable commercial applications. The key to success is to test assumptions through real‐life experiments – for example, market assumptions should be tested in‐market, manufacturability assumptions should be tested in production.

Firms should adopt assumption‐driven learning in a series of sequential divergent‐convergent cycles – one cycle per stage – each centered on testing the major assumptions for that stage.

The author developed a theory of optimal trajectories for air vehicles with variable wing area and conventional wings. He applied a new theory of singular optimal solutions and obtained the optimal flight in many cases. At first glance, the results may seem strange however, this is correct and this paper will show how this new theory may be used. The main idea of the research is in using the vehicle's kinetic energy for increasing the range of missiles and projectiles. The author shows that the range of a ballistic warhead can be increased 3‐4 times if an optimal wing is added to the ballistic warhead, especially a wing with variable area. If increased range is not needed, the warhead mass can be increased. The range of big gun shells can also be increased 3‐9 times. The range of aircraft may be improved 3‐15 percent and more. The results can be used for the design of aircraft, missiles, flying bombs and shells of big guns.

One of the characteristics of the 1979 Paris Salon was a greater emphasis on civil aviation then had been apparent for some years. Not only did this feature make itself known by the presence of two A300's and other types but major manufacturers set out to provide the maximum information about future products and systems, many of the latter not being well‐known outside their country of origin.

It was a good Farnborough Show … for those who went to see the flying displays and the weather was a great consolation. But it was an unusual Farnborough in some respects, first because of the good weather and this does bear repetition, and it does make such a difference to setting up the Show to its progress through the week and to the mood of the people there.