The vision for this research is to develop a novel toolset for flight simulation fidelity enhancement. This represents a step-change in simulator qualification, is well-timed making a significant contribution to the UoL initiated NATO STO AVT-296-RTG activity and will have an immediate impact through engagement with Industry partners. High fidelity modelling and simulation are prerequisites for ensuring confidence in decision making during aircraft design and development, including performance and handling qualities estimation, control law development, aircraft dynamic loads analysis, and the creation of a realistic piloted simulation environment. The ability to evaluate/optimise concepts with high confidence and stimulate realistic pilot behaviour are the kernels of quality flight simulation, in which pilots can train to operate aircraft proficiently and safely and industry can design with lower risk. Regulatory standards such as CS-FSTD(H) and FAA AC120-63 describe the certification criteria and procedures for rotorcraft flight training simulators. These documents detail the component fidelity required to achieve "fitness for purpose", with criteria based on "tolerances", defined as acceptable differences between simulation and flight, typically +/- 10% for the flight model. However, these have not been updated for several decades, while on the military side, the related practices in NATO nations are not harmonised and have often been developed for specific applications. Methods to update the models for improved fidelity are mostly ad-hoc and, without a strong scientific foundation, are often not physics-based. This research will provide a framework for such harmonisation removing the barriers to adopting physics-based flight modelling and will create new, more informed, standards. In this research two aspects of fidelity will be tackled, predictive fidelity (the metrics and tolerances in the standards) and perceptual fidelity (pilot opinion). The predictive fidelity aspect of the research will use System Identification techniques to provide a systematic framework for 'enhancing' a physics-based simulation model. The perceptual fidelity research will develop a rational, novel process for task-specific motion tuning together with a robust methodology for capturing pilots' subjective assessment of the overall fidelity of a simulator. Extensive use will be made of flight simulation and real-world flight tests throughout this project in both the predictive and perceptual fidelity research.

Oil crops are one of the most important agricultural commodities. In the U.K. (and Northern Europe and Canada) oilseed rape is the dominant oil crop and worldwide it accounts for about 12% of the total oil and fat production. There is an increasing demand for plant oils not only for human food and animal feed but also as renewable sources of chemicals and biofuels. This increased demand has shown a doubling every 8 years over the last four decades and is likely to continue at, at least, this rate in the future. With a limitation on agricultural land, the main way to increase production is to increase yields. This can be achieved by conventional breeding but, in the future, significant enhancements will need genetic manipulation. The latter technique will also allow specific modification of the oil product to be achieved. In order for informed genetic manipulation to take place, a thorough knowledge of the biosynthesis of plant oils is needed. Crucially, this would include how regulation of oil quality and quantity is controlled. The synthesis of storage oil in plant seeds is analogous to a factory production line, where the supply of raw materials, manufacture of components and final assembly can all potentially limit the rate of production. Recently, we made a first experimental study of overall regulation of storage oil accumulation in oilseed rape, which we analysed by a mathematical method called flux control analysis. This showed that it is the final assembly that is the most important limitation on the biosynthetic process. The assembly process requires several enzyme steps and we have already highlighted one of these, diacylglycerol acyltransferase (DGAT), as being a significant controlling factor. We now wish to examine enzymes, other than DGAT, involved in storage lipid assembly and in supply of component parts. This will enable us to quantify the limitations imposed by different enzymes of the pathway and, furthermore, will provide information to underpin logical steps in genetic manipulation leading to plants with increased oil synthesis and storage capabilities. We will use rape plants where the activity of individual enzymes in the biosynthetic pathway have been changed and quantify the effects on overall oil accumulation. To begin with we will use existing transgenic oilseed rape, with increased enzyme levels, where increases in oil yields have been noted; these are available from our collaborators (Canada, Germany). For enzymes where there are no current transgenic plants available, we will make these and carry out similar analyses. Although our primary focus is on enzymes that increase oil yields, we will also examine the contribution the enzyme phospholipid: diacylglycerol acyltransferase (PDAT) makes to lipid production because this enzyme controls the accumulation of unsaturated oil, which has important dietary implications. In the analogous model plant Arabidopsis, PDAT and DGAT are both important during oil production. Once we have assembled data from these transgenic plants we will have a much better idea of the control of lipid production in oilseed rape. Our quantitative measurements will provide specific targets for future crop improvements. In addition, because we will be monitoring oil yields as well as flux control we will be able to correlate these two measures. Moreover, plants manipulated with multiple genes (gene stacking) will reveal if there are synergistic effects of such strategies. Because no one has yet defined quantitatively the oil synthesis pathway in crops, data produced in the project will have a fundamental impact in basic science. By combining the expertise of three important U.K. labs. with our world-leading international collaborators, this cross-disciplinary project will ensure a significant advance in knowledge of direct application to agriculture.

Modern aeroplanes are well equipped to cope with most common icing conditions. However, some conditions consisting of supercooled large droplets (SLD) have been the cause of tragic accidents over the last three decades. It was proven that there are certain types of aircraft which are not robust against these conditions as ice can form on unprotected areas of the lifting surfaces leading to loss of control. Consequently, authorities addressed these safety concerns by issuing new certification rules under Appendix O to ensure that future aircraft remain controllable in these conditions and can exit safely upon detection. Hence, the key to increasing overall aviation icing safety is the early and reliable detection of icing conditions to allow the necessary actions to be taken by the flight crew. SENS4ICE (SENSors and certifiable hybrid architectures for safer aviation in ICing Environment) directly addresses this need for reliable detection and discrimination of icing conditions. It proposes that an intelligent way to cope with the complex problem of ice detection is the hybridisation of different detection techniques: direct sensing of atmospheric conditions and/or ice accretion on the airframe, combined with indirect techniques in which the change of aircraft characteristics with ice accretion on the airframe is detected. SENS4ICE will address the development, test, validation, and maturation of the different detection principles, the hybridisation - in close cooperation with regulators to provide an acceptable means of compliance - and the final airborne demonstration of technology capabilities in relevant natural icing conditions. The contribution of SENS4ICE to increase aviation safety will be achieved by an international consortium of 20 partners (13 EU, 7 non-EU) with contributions from Brazil, Canada, Russia and the US. The 4-year project requests an overall EU-funding of 6.6M€ and benefits from a further 5.4M€ of activities being provided by the non-EU partners.