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Cambridge, United Kingdom

Guided wave inspection is a fast growing technology for screening pipelines for corrosion. The technique is capable of inspecting tens of metres from a single test location and examining otherwise inaccessible regions of pipeline such as cased road crossings. However, enhancements to the technique are needed if inspections are to be transformed from a screening procedure to a more quantitative assessment of the condition of the pipeline. A rapid calculation procedure to determine the dispersion curves for guided wave modes is important if enhancements are to be automatically incorporated into the technique. Commercial code for dispersion curve calculation is available but it is proprietary and typically uses an iterative procedure to calculate curves which can be unreliable and slow. Other methods for calculating dispersion curves have been published including semi-analytical finite element solutions but these require extensive programming. In this paper, a closed form solution based on known trigonometric behaviour in the circumferential and axial directions and a standard polynomial solution through the thickness is presented. The method allows rapid computation of dispersion curves for typical guided wave inspection scenarios with minimal programming required. In addition, a tracing algorithm is also presented which allows the computed points to be joined to form curves and therefore fully identify the dispersive behaviour of each wave mode. The new method has been successfully verified against the well-established software, Disperse®, for a range of pipe sizes, materials and frequencies typical to guided wave inspection. © 2014 Elsevier B.V. Source


Grant
Agency: Cordis | Branch: H2020 | Program: CS2-RIA | Phase: JTI-CS2-2014-CFP01-AIR-02-06 | Award Amount: 694.09K | Year: 2016

Resin Transfer Moulding (RTM) involves moderate pressure resin injection of a dry preform placed in sealed rigid tooling. Fast and effective processing requires correct placement of the reinforcement to avoid defects and potential race tracking, appropriate selection of inlet and outlet locations, and careful control of flow speeds to minimise porosity and dry regions; furthermore, suitable cure conditions are needed to avoid under-cure, or exothermic effects that generate excessive residual stresses and final part distortions. Today, finite element simulation is regularly used to design injection processes and cure. However, purely predictive simulation suffers from issues related to uncertainty and variability in material state and numerous process variables. Online monitoring of resin flow in tests and stochastic simulations to understand effects of material and model variability on flow processes could be two methods to enhance fidelity of numerical simulation models. The proposed project integrates three approaches to provide a unified integrated simulation tool combining predictive modelling, variability propagation and process monitoring. Input utilises material data and models to be developed with physical resin sensor results, from which process outcomes, conditional on material and process variables, are determined. The proposed work develops this concept for the three stages of RTM processing; namely, preforming, injection and cure. The overall concept will be implemented on a pilot RTM line and then transferred to the Topic Managers manufacturing site, where it will be used for trials. The project combines two universities with specialist knowledge in fabric mechanical and permeability modelling, resin test and modelling and numerical simulation of RTM processes and final part distortion. One industrial partner collaborates on industrial RTM and flow monitoring.


Grant
Agency: Cordis | Branch: H2020 | Program: RIA | Phase: MG-1.10-2015 | Award Amount: 2.19M | Year: 2016

This proposal is in response to the call for International Cooperation in Aeronautics with China, MG-1.10-2015 under Horizon 2020 Enhanced Additive Manufacturing of Metal Components and Resource Efficient Manufacturing Processes for Aerospace Applications. The objectives are to develop the manufacturing processes identified in the call: (i) Additive manufacturing (AM); (ii) Near Net Shape Hot Isostatic Pressing (NNSHIPping) and (iii) Investment Casting of Ti alloys. The end-users specify the properties and provide computer-aided design, (CAD) files of components and these components will be manufactured using one or more of the three technologies. During the research programme, experiments will be carried out aimed at optimising the process routes and these technologies will be optimised using process modelling. Components manufactured during process development will be assessed and their dimensional accuracies and properties compared with specifications and any need for further process development identified. The specific areas that will be focussed on include: (a) the slow build rate and the build up of stresses during AM; (b) the reproducibility of products, the characteristics of the powder and the development of reusable and/or low cost tooling for NNSHIP; (c) the scatter in properties caused by inconsistent microstructures; (d) improving the strength of wax patterns and optimising welding of investment cast products. The process development will be finalised in month 30 so that state-of-the-art demonstrators can be manufactured and assessed by partners and end-users, during the final 6 months. The cost of the process route for components will be provided to the end-users and this, together with their assessment of the quality of these products, will allow the end-users to decide whether to transfer the technologies to their supply chain. The innovation will come through application of improved processes to manufacture the demonstrator components.


Grant
Agency: Cordis | Branch: H2020 | Program: IA | Phase: EeB-01-2014 | Award Amount: 6.32M | Year: 2015

The ISOBIO project will develop a new approach to insulating materials through the novel combination of existing bio-derived aggregates with low embodied carbon with innovative binders to produce durable composite construction materials. These novel composites will target 50% lower embodied energy and carbon than traditional oil based insulation panels, and will increase thermal insulation compared with traditional systems by at least 20%. By using bio-based materials, using vertical integration from raw material production through to finished systems, the ISOBIO project aims to reduce costs by at least 15% over traditional systems. The use of bio-based materials ensures that whole life energy use is reduced through taking advantage of the photosynthesis of atmospheric carbon which is sequestered in the fabric of the building for its lifetime. The ISOBIO materials take advantage of the natural moisture sorption/desorption characteristics of bio-based materials, which is known to passively manage the indoor environment resulting in greatly improved indoor air and environmental quality, whilst at the same time reducing the demand for air conditioning.


Grant
Agency: Cordis | Branch: H2020 | Program: IA | Phase: FTIPilot-1-2015 | Award Amount: 2.79M | Year: 2016

The EU Agency for Safety & Health is currently amending wind turbine standards (such as EN 50308) to ensure safer O&M tasks and increase the Probability Of Detection (POD) for wind turbine defects. ISO have also identified such issues, and in fact initiated the development of QA standards specifically tailored for the Condition Monitoring (CM) of wind turbines. Current CM systems are intrusive, and hence revoke the initial OEM warranty of drive-train components. The combination of industrial and legislative factors is the key driver behind the production of CMDrive: a bespoke and non-intrusive acoustic-analysis CM system, having a POD for drive-train defects of 90-98% within the range of operating powers. The requested grant of 2.5m will be required to validate and enhance the system, and initiate the commercialisation process. Growth in the wind services sector, as related to O&M and CM, is also compelling, as studies by Deloitte have shown that the corresponding market is estimated to increase from 5.2b to 10.8b by 2020, with a CAGR of 10%. The first generation of CMDrive shall be produced for wind turbines of 2.5MW or less; a next generation product, to handle larger turbines, has already been envisioned. The commercialisation strategy involves the segmentation of the wind turbine market into 3 initial customer tiers, is targeting WFOs and Independent Service Providers of CM within such tiers, and will position the product through a number of Unique Selling Points, which will be elaborated further in this proposal. The locations of the 5 partners, in addition to the global outreach of TWI and INESCO, are critical factors for launching the product by 2019. It is expected that CMDrives associated revenue streams (sales, services, licensing) will yield an estimated ROI of 1100%, and corresponding cumulative profits of 26m, over the 5 year forecast (20192023). INESCO will take lead of the sales, with the other partners benefiting by means of profit shares.

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