Systems and certification issues for civil transport aircraft flow control systems

This article is placed here with permission from the Royal Aeronautical Society - Copyright @ 2009 Royal Aeronautical SocietyThe use of flow control (FC) technology on civil transport aircraft is seen as a potential means of providing a step change in aerodynamic performance in the 2020 time frame. There has been extensive research into the flow physics associated with FC. This paper focuses on developing an understanding of the costs and design drivers associated with the systems needed and certification. The research method adopted is based on three research strands: 1. Study of the historical development of other disruptive technologies for civil transport aircraft, 2. Analysis of the impact of legal and commercial requirements, and 3. Technological foresight based on technology trends for aircraft currently under development. Fly by wire and composite materials are identified as two historical examples of successful implementation of disruptive new technology. Both took decades to develop, and were initially developed for military markets. The most widely studied technology similar to FC is identified as laminar flow control. Despite more than six decades of research and arguably successful operational demonstration in the 1990s this has not been successfully transitioned to commercial products. Significant future challenges are identified in cost effective provision of the additional systems required for environmental protection and in service monitoring of FC systems particularly where multiple distributed actuators are envisaged. FC generated noise is also seen as a significant challenge. Additional complexity introduced by FC systems must also be balanced by the commercial imperative of dispatch reliability, which may impose more stringent constraints than legal (certification) requirements. It is proposed that a key driver for future successful application of FC is the likely availability of significant electrical power generation on 787 aircraft forwards. This increases the competitiveness of electrically driven FC systems compared with those using engine bleed air. At the current rate of progress it is unlikely FC will make a contribution to the next generation of single-aisle aircraft due to enter service in 2015. In the longer term, there needs to be significant movement across a broad range of systems technologies before the aerodynamic benefits of FC can be exploited.This work is supported by the EU FP6 AVERT (AerodynamicValidation of Emissions Reducing Technologies) project

Structural Material Property Tailoring Using Deep Neural Networks

Advances in robotics, artificial intelligence, and machine learning are ushering in a new age of automation, as machines match or outperform human performance. Machine intelligence can enable businesses to improve performance by reducing errors, improving sensitivity, quality and speed, and in some cases achieving outcomes that go beyond current resource capabilities. Relevant applications include new product architecture design, rapid material characterization, and life-cycle management tied with a digital strategy that will enable efficient development of products from cradle to grave. In addition, there are also challenges to overcome that must be addressed through a major, sustained research effort that is based solidly on both inferential and computational principles applied to design tailoring of functionally optimized structures. Current applications of structural materials in the aerospace industry demand the highest quality control of material microstructure, especially for advanced rotational turbomachinery in aircraft engines in order to have the best tailored material property. In this paper, deep convolutional neural networks were developed to accurately predict processing-structure-property relations from materials microstructures images, surpassing current best practices and modeling efforts. The models automatically learn critical features, without the need for manual specification and/or subjective and expensive image analysis. Further, in combination with generative deep learning models, a framework is proposed to enable rapid material design space exploration and property identification and optimization. The implementation must take account of real-time decision cycles and the trade-offs between speed and accuracy

Frontiers of Adaptive Design, Synthetic Biology and Growing Skins for Ephemeral Hybrid Structures

The history of membranes is one of adaptation, from the development in living organisms to man-made versions, with a great variety of uses in temporary design: clothing, building, packaging, etc. Being versatile and simple to integrate, membranes have a strong sustainability potential, through an essential use of material resources and multifunctional design, representing one of the purest cases where “design follows function.” The introduction of new engineered materials and techniques, combined with a growing interest for Nature-inspired technologies are progressively merging man-made artifacts and biological processes with a high potential for innovation. This chapter introduces, through a number of examples, the broad variety of hybrid membranes in the contest of experimental Design, Art and Architecture, categorized following two different stages of biology-inspired approach with the aim of identifying potential developments. Biomimicry, is founded on the adoption of practices from nature in architecture though imitation: solutions are observed on a morphological, structural or procedural level and copied to design everything from nanoscale materials to building technologies. Synthetic biology relies on hybrid procedures mixing natural and synthetic materials and processes

A comparison of processing techniques for producing prototype injection moulding inserts.

This project involves the investigation of processing techniques for producing low-cost moulding inserts used in the particulate injection moulding (PIM) process. Prototype moulds were made from both additive and subtractive processes as well as a combination of the two. The general motivation for this was to reduce the entry cost of users when considering PIM. PIM cavity inserts were first made by conventional machining from a polymer block using the pocket NC desktop mill. PIM cavity inserts were also made by fused filament deposition modelling using the Tiertime UP plus 3D printer. The injection moulding trials manifested in surface finish and part removal defects. The feedstock was a titanium metal blend which is brittle in comparison to commodity polymers. That in combination with the mesoscale features, small cross-sections and complex geometries were considered the main problems. For both processing methods, fixes were identified and made to test the theory. These consisted of a blended approach that saw a combination of both the additive and subtractive processes being used. The parts produced from the three processing methods are investigated and their respective merits and issues are discussed

Integration of decision support systems to improve decision support performance

Decision support system (DSS) is a well-established research and development area. Traditional isolated, stand-alone DSS has been recently facing new challenges. In order to improve the performance of DSS to meet the challenges, research has been actively carried out to develop integrated decision support systems (IDSS). This paper reviews the current research efforts with regard to the development of IDSS. The focus of the paper is on the integration aspect for IDSS through multiple perspectives, and the technologies that support this integration. More than 100 papers and software systems are discussed. Current research efforts and the development status of IDSS are explained, compared and classified. In addition, future trends and challenges in integration are outlined. The paper concludes that by addressing integration, better support will be provided to decision makers, with the expectation of both better decisions and improved decision making processes