Blogs

125 years later, the Royal Navy launched Holland 1. Described by Military History Matters as “the first recognisably modern submarine”, Holland 1 (or ‘HM submarine Torpedo Boat No. 1’) took an eight-man crew and could carry three 18-inch torpedoes. Underwater craft have come a very long way in the twenty-five decades since Turtle’s deployment.

Operating in a highly challenging and unforgiving environment, the need for absolute engineering excellence for today’s submarines is paramount. Submarines play a hazardous game of hide and seek against enemies equipped with increasingly sophisticated and novel sensors. As a result, submarines must be designed to be as stealthy as possible across a very wide frequency spectrum, and regularly tested both during design before being accepted and once in service to ensure that they remain this way. In a 2021 news story published by the Ministry of Defence, Ian Booth, the then CEO of the UK’s Submarine Delivery Agency described the design and construction of such vessels as: “…one of the most complex and challenging feats of engineering that the maritime industry undertakes”. Of course, as well as submarines, modern underwater military system providers are continually developing and exploiting emerging technologies, uncrewed systems for example, to increase their effectiveness.

QinetiQ and its predecessors have been involved in Test and Evaluation (T&E) in the maritime domain for over 100 years. This heritage, alongside our experience, gives us a unique insight into the future of T&E in this challenging domain. It is, of course, hard to know precisely what the future will bring, but throughout this series of articles, we will explore multiple areas of development, based on the extrapolation of current trends.

The Adoption of Digital Engineering

Stealth is one of the most, if not the most, critical characteristic that future underwater platforms must achieve to ensure continuing operational effectiveness. This must be delivered against the continual development of improved technologies to detect conventional signatures and the development of novel modes of underwater platform detection, both of which are happening at pace. Matching this pace will see the increased convergence of several emergent themes; digital twinning and data analytics underpinned by increasingly complex modelling and critical live testing.

Digital twinning, driven by improvements in computational power and storage, is defined by IBM as ‘a virtual representation of an object or system that spans its lifecycle, is updated from real-time data, and uses simulation, machine learning and reasoning to help decision-making.’ It is currently more prominent in the civil industry than defence, where digital twins are used to provide predictive diagnostics for jet engines for example. Integration of data from suitable sensors into a digital twin of a maritime platform could provide a real-time insight into emergent signature issues. The confidence in this process will be underpinned by the validation of the physics embodied in the predictive tools that exploit the digital twin to generate signature insights. This will shift the emphasis of live testing from one of direct signature measurement to validation of the physical processes that map platform features to detectable effects. However, it is worth reflecting on the complexity of a modern submarine and resulting difficulty in the successful realisation of this approach.

This leads to the second enabler: data analytics and machine learning. Many of these physical processes are highly complex and trying to embody them directly in conventional physics-based modelling will be increasingly challenging. However, the integration of data from physical measurement both at full-scale and sub-scale, computational modelling and historical measurements provides a large data base to which modern tools can be applied to ‘learn’ and embody the physics. Computational Fluid Dynamics (CFD) and other approaches can be expected to grow in effectiveness and areas of use. However, physical experimentation, including sub-scale, will be needed to increase confidence in the predictions of modelling - as well as address the issues currently (and for the foreseeable future) that are beyond synthetic modelling’s capability.

Both of these initiatives fall under the purview of digital engineering and exploit the benefits of much more deeply integrating test data derived throughout the design, development and deployment of the platform. Consideration of the lifecycle holistically allows for the balance of sub-scale, full-scale and computational techniques to be tuned in-line with risks and unknowns. For example, the need for new forms of instrumentation to understand and quantify phenomena that are poorly understood. As synthetic approaches then improve, experiments will be needed to validate new modelling techniques or assess novel designs where the confidence in the modelling has yet to be established. This deep integration will be key to understanding and mitigating the performance of new technologies designed to detect very stealthy, but large masses, moving under the sea-surface.

To conclude, the movement away from live testing towards increasingly sophisticated digital modelling techniques will be of considerable note in coming years. Whilst the increased adoption of digital engineering will never fully mitigate the need to perform essential live testing exercises, the elevated use of data in underwater T&E will improve the pace at which new technologies, such as uncrewed underwater platforms, can be accepted into service. In the next article in this series, we will explore the increased use of uncrewed platforms in the underwater domain, and how T&E will adapt to this future trend.