Non-destructive testing (NDT) is essential for ensuring and maintaining the integrity of structures and systems from aircraft to power stations. NDT operators are trained by practising on specimens with real or artificial flaws. These samples can be rare and/or expensive. For training at clients’ premises, NDT trainers must carry samples to the training location. The shear bulk and weight of the samples turns the provision of training into a major logistical exercise, and in some cases makes it impractical. This project will develop a new system which uses real data to provide an NDT experience indistinguishable from the real one, but without the need for the test sample. The system integrates wireless position sensors, gyroscopic orientation, camera input and load sensing into a hand-held probe. TrainNDT will develop an integrated sensor platform and construct the virtual environment based on real test data from well-defined samples with a range of defects. Software will relate the recorded NDT data to the real-time probe position, orientation, and pressure to output a signal to the trainee as if they were testing the real sample. Benefits include: the ability to carry out training anywhere in the world without the need for costly transportation of test specimens; availability of a much wider variety of virtual test specimens; and the ability to vary the training programme at short notice simply by downloading a new dataset. The system can provide automated checks and feedback on the trainee’s probe movements based on actual movements, adding value to the training experience.

The goal is to achieve nondestructive inspection (NDI) of nuclear power generation and reprocessing plant pipework carrying cooling water or generator steam, along pipe runs that are embedded in concrete, buried underground and/or clad in protective coatings such as plastic or bitumen. Key examples are (i) primary coolant and steamline pipework passing respectively through the concrete primary and secondary containment walls; and (ii) pipework for spent fuel cooling. Any breach of these pipes carries risks of nuclear radiation leakage and shut down for repair. Embedding/cladding materials all highly attenuate ultrasound, making current ultrasonic NDI practice in nuclear plant unusable or requiring cladding removal. The innovative solution is to use low frequency guided ultrasonics (LFGU), which can propagate through embedding and cladding materials, in both periodic inspection and continuous structural health monitoring modes. Enhanced signal to noise ratios through new high power transducers and low noise receiver combined with advanced signal processing for trend analysis will allow detection of smaller crack and corrosion defects than hitherto possible by LFGU.

MarBN steels are the most promising approach to increasing the temperature capability of creep resistant martensitic steels to above 620 C. Previously, MarBN steel has been successfully developed in the TSB project, IMPACT (2010-2013) and showed significant improvements in creep strength (20-40%) compared to the current state-of-the-art steels, Grade 92 and CB2. It is essential as the next stage of material introduction to upscale and demonstrate the manufacturability of industrial components and the INMAP project will develop and validate the casting technology and NDT inspection procedures required to produce a demonstration component . The key technology for non-destructive tests (NDT) with enhanced detectability for this compositionally complex steel will be developed. Weld repair for the casting component will be applied if any surface defects exist. Finally the integrity of the casting will be characterised through extensive mechanical tests including creep and low cycle fatigue (LCF) to establish that the benefit apparent from laboratory tests is maintained in industrial components.

Hull fouling is the largest contributor to excess fuel consumption and carbon emissions by ships, which can be up to 50% over a year. In spite of a global expenditure of some £6bn pa on fouling prevention and cleaning amongst the global merchant fleet, fouling still costs £8bn pa in additional fuel costs and produces 70m tonnes of additional carbon dioxide. The project goal is to develop an in service automated system for permanent fouling prevention, detection and removal based on a distributed, sparse network of low frequency (~40kHz) active ultrasonic compressional wave sensors embedded in a ship hull. In normal operation, temporary but continuous quasi forced standing waves will be excited throughout the hull, with power sufficient for ultrasound leakage into water from surface antinodes to produce cavitation. Cavitation will remove thin biofilms (i.e. microfouling) and their adhesion surface as fast as they are formed, thus preventing fouling build-up i.e. macrofouling. The frequency will be swept and different parts of the network sequentially excited scan the antinodes through 100% of the hull. This programme will remove biofilm over 100% of the hull and propeller surface, with minimum ON/OFF time for the continuous waves i.e. minimum time averaged power. Periodically, pulsed waves will be excited to detect accidental macrofouling up caused by imperfect biofilm removal, which will then be removed by a temporary increase in the continuous ON/OFF time followed by a return to normal operation. There exists the possibility, to be researched that the intial formation of biofouling can be prevented by ultrasonic force fields at sub-cavitation levels, further reducing the average power consumption.

There are 29,000km of high voltage overhead transmission cables in the UK, operating in severe conditions of heat and cold, moisture, voltage stress, wind induced vibration, overloads and structural fatigue, all of which can cause catastrophic failure. The MOSAIC project aims to prototype a novel method of combined monitoring and enhancement of the structural health of these cables, more technically effective, cost effective and safer than existing passive monitoring techniques i.e. infra-red and visual imaging using helicopters and human inspectors. In the MOSAIC technology one sensor module, in a fixed location on a cable and self-powered by inductive harvesting of energy from the cable, will permanently and in real time monitor a cable to: (1) Measure vibrations, which are a major cause of cable fatigue, and actively cancel them through automatic electromechanical means. (2) Actively detect early signs of cable fatigue and track its growth using long range guided ultrasound, which can access cable areas impossible with infrared and visual sensing. (3) Wirelessly transmit essential data including cable location to a base station, for instant maintenance decision making.