A fully digitalised development process, from the conception phase of a new product and throughout its life cycle, with benefits in terms of costs, time and risks: this is the digital twin revolution, achieved through the large-scale use of disruptive technologies such as supercomputing, cloud-computing and artificial intelligence. In this context, Leonardo has developed an “agile” paradigm of digitalisation of design processes that, through the creation of a virtual environment based on Model Based System Engineering (MBSE), allows a digital version of the product to be conceived, verified, “assembled” and configured.
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How the digital twin is changing design
Reproducing a physical object, an entire system or a “system of systems” in an entirely virtual environment, with a high degree of reliability, is the concept behind the “digital twin”, the most advanced frontier of digitalisation. The software architecture that makes this type of simulation possible is the meta-simulator, operating in Leonardo's PC2Lab in Turin.
Model Based System Engineering
Model Based System Engineering is the approach methodology for system modelling, which allows the creation and animation of a digital model of a certain system to observe how it operates even before it is built.
The help of the digital twin is fundamental from the earliest phases of system planning and design. It can be used to experiment, elaborate, and test models that can predict the characteristics and behaviour of the machine being designed, with an increasing level of detail and progressively reaching an absolutely realistic representation. This process, which includes a much more precise simulation compared to that of the traditional approach, allows designers to virtualise and anticipate the validation of systems under development by providing them with accurate and reliable models that they can rely on, integrating the contributions of all players involved in the development process - including the supply chain - within a single environment.
The innovation of the PC2Lab
Leonardo's PC2Lab (Product Capability and Concept Laboratory) is a multifunctional and multi-domain laboratory in Turin. It is based on the development and integration of software, hardware, technologies, algorithms, and models in a completely synthetic environment (Model Based System Engineering), in which tactical scenarios and missions are developed, simulated and studied.
Born with the aim of supporting the Aircraft business area in defining new aeronautical operating concepts, it differs from Leonardo's first Battle Lab and the most common tactical scenario simulators. Compared to the traditional approach, the PC2Lab includes virtual and real components within the simulated scenario, with a Live Virtual Constructive (LVC) approach that enables real-time, simulated and real-life demonstrations to be carried out at the same time.
The Leonardo Battle Lab and the GCAP programme
The Battle Lab is a laboratory that combines physical systems, synthetic reality and immersive reality organised around three primary components: the scenario generator, the Smart Chair (virtual reproduction of the aircraft cockpit) and the Prototyping Pilot Station (a “powered mock-up” of the M-346 aircraft cockpit representing an instance of a combat aircraft on which to conduct experiments), all interconnected and able to be linked up with simulators and external laboratories.
Within it, the enabling technologies are created for the development of the Global Combat Air Programme (GCAP), an international collaboration programme involving Italy, the United Kingdom and Japan, with the shared ambition of developing a next-generation aircraft system by 2035. Defined as a “system of systems”, it will operate in the five domains (air, land, sea, space and cyber), according to a stellar structure in which the next generation fighter will be the “core platform”, connected to uncrewed gregarious aircraft (known as “adjuncts”).
The laboratory consists of several components – the Smart Chair, the Prototyping Pilot Station and the meta-simulator, based on elements of innovation and high technology – and uses advanced AI algorithms and the capability of the davinci-1 supercomputer to execute refined simulations. These can be used to verify the characteristics of an already existing aircraft or one in the process of being defined, and validate its effectiveness in the operational scenarios in which it will be used.
The Smart Chair and the Prototyping Pilot Station are equipped with advanced interfaces with Virtual and Extended Reality, functions for flight and mission autonomy and for experimental pilot digital assistance systems. The presence of these technologies in the same simulation environment, which is highly complex and integrated in order to be realistic for the user (the pilot), can be used to develop a multi-domain and multi-asset project in a coordinated way, validating it step by step.
Leonardo’s Smart Chair
Behind the scenes is the laboratory’s new engine, the meta-simulator, which is the infrastructure that “supports” the digital twin from the very early stages of its conception. Defined as a “project digital twin”, it can be used to configure the ideal aircraft model, testing individual parts or multiple components (engine, flight controls, avionics, aerodynamics, etc.) in a coordinated way. Through this process, models of the overall aircraft and its components are created well before they are given physical form.
Meta-simulator
The meta-simulator is the representation of the digital ecosystem based on the MBSE methodology. In other words, it is the IT device that can be used to develop a project based on models created with the MBSE methodology.
Initially very simplified and linearised, these models become progressively more sophisticated, providing increasingly large volumes of increasingly accurate data and requiring greater computing power. All on-board systems are synchronised to form a realistic and consistent model, which allows the detailed simulation of a complex system. This is then inserted into the chosen scenario to verify its performance and effectiveness in relation to the tasks assigned to the system itself.
By varying the parameters relating to the possible and foreseeable characteristics of the machine, the process allows the execution of numerous differing simulation exercises. Once analysed, the data generated from the scenario simulations are the basis for calibrating the capabilities of a single or multiple aircraft (the mother fighter and its uncrewed adjuncts) in terms of speed, range, payload, sensors, etc., and for optimising its/their configuration without having to wait for the development of real hardware and flight tests.
How do the simulation exercises work?
After setting up a scenario with all the expected “players” (fighters, uncrewed systems, control station, defence systems, ships, ground systems, satellites, etc.), its evolution is observed during a run (a simulation in which an entire scenario is played out, starting from an initial state and evolving during the mission).
The exercises can be fully automatic runs, generally in accelerated time, or runs in real time, with the participation of human players (a pilot in a simulator) to evaluate the performance and effectiveness of the system being defined (for example, the mother fighter with its adjuncts). During these exercises, different alternatives are explored in order to evaluate the most effective ones for possible subsequent development
The entire process is based on an “agile” approach. Working in small groups, experienced specialists in different disciplines set very short and tightly scheduled objectives to monitor the status of the project through constant checks and demonstrations. This approach significantly reduces development times and quickly arrives at a proposal for a solution to be evaluated and progressively improved during so-called “sprints” (phases of the project in which the team works to achieve progress within a short space of time, for example two weeks, setting an objective and creating a demo to verify the results after a defined deadline). The aim is to achieve a true “digital first flight” of an aircraft that does not yet physically exist, generating a reduction in risk and greatly shortening development times.
Simulation mode, between real and virtual
After an entirely virtual first phase, “mixed” experiments take place, i.e. with the presence of virtual and real elements. These involve the use of technologies derived from the training sector, such as augmented reality and Live-Virtual-Constructive simulation. This technology can connect aircraft in the air with simulators on the ground, immersed in a unique synthetic environment that provides a highly sophisticated representation of the scenario thanks to the exchange of information, through data links, between real and virtual players.
An example of this mixed-approach technology is the CUC-T demonstration (Crewed-Uncrewed Teaming, which involves cooperation between manned and unmanned aircraft), part of the national technology development roadmap for the GCAP programme. An M-346 aircraft, in core platform role, flies with the pilot who controls virtual adjunct aircraft (meta-simulators) in the rear cockpit. This CUC-T “team” operates in the same scenario generated also on the ground, where another pilot on a core platform simulator is able to participate in the same exercise.
Working in parallel, the test pilots are able to verify the adequacy of the experimental management system of the various adjuncts, evaluating the level of autonomy that, combined with the advanced pilot digital assistance tools, should ensure a manageable workload level.
The timely definition of these parameters is essential since their impact directly affects the project, including the human-machine interface. This is because they are linked to crucial aspects such as the optimal layout of controls and buttons, the configuration of headsets, and the selection of the most relevant information to be shown to the pilot at each stage of the mission.
An Open Innovation system
To nurture PC2Lab's vocation for innovation, a laboratory entirely dedicated to artificial intelligence is active in Turin, where a pool of young students, professionals and AI experts collaborate with Leonardo Labs in an Open Innovation setting. The objective is to develop artificial intelligence algorithms, building them and testing their effectiveness in a simplified environment before they converge in the PC2Lab, the first multifunctional integration laboratory.
This ecosystem is aimed at the development of increasingly advanced technologies and is based on a collaboration built on many components. One valuable resource among these is academia, with students from Italian and international universities gaining initial experience of the company (through an internship, a graduate thesis or a doctorate programme) and then, after completing their studies, having the possibility to continue their journey as employees.