Navigating the Skies of Innovation: How HPC and AI Propel the Fighter Aircraft Development Lifecycle

We all have heard the famous quote, “It’s about the pilot, not the plane” (unless you are in a Cessna-152 against an F-35, ofcourse). In the movie ‘Top Gun’, this idea is exemplified as pilots rely on their skills and instincts to push their aircraft to the limits. But what is it that gives a pilot confidence that the aircraft will respond precisely to their commands, that its limits can be pushed with calculated risks, and that the machine can be trusted with their life? In this blog we discover what type of computational work is carried out in the development of fighter aircraft with examples from top 10 global aerospace and new space companies, who face similar challenges in this industry.

Whether it’s a Formula 1 racecar, an olympic track cycling bike or a fighter aircraft; they inherently belong to a class of high performance machines that require precise enhancements both in their material and the way the structure interacts with the operating environment. The smallest change in the right tactical area can make the largest difference in the specific performance criteria but how do you find and implement that smallest change?

My visit to Farnborough Airshow this year was filled with exciting discussions with numerous industry innovators.  To name a few, this involved discussions with commercial aircraft manufacturers, eVTOL manufacturers, defense manufacturers and the supporting software ecosystem, amongst various others in the industry. I was particularly thrilled to learn about the fighter aircraft and the extensive computational work involved in their development, operations, and maintenance. Highly advanced multi-role combat aircrafts like the ‘Eurofighter Typhoon’ are equipped with numerous onboard computers to manage sophisticated avionics, flight control systems, sensors, and weapons. With this, I want to explore the development of fighter aircraft, highlighting the latest AI technologies and how companies like Rescale support this ecosystem.

Developing a Fighter Aircraft

Developing a fighter aircraft is a complex and multi-stage process that heavily relies on refined outputs using advanced simulation software. A variety of simulation software is utilized in various stages of the development, operations and maintenance of a fighter aircraft. Such software often requires scalable high-performance computing power to handle large quantities of data and compute cycles, with application of AI in refining simulations for different stages of the process. 

Simulation Software and AI Enhancements

Simulation software is an integral part of the entire lifecycle of fighter aircraft development. It enhances the design accuracy, reduces the costs, and speeds up the development process by allowing extensive testing and validation in a virtual environment before physical prototypes are built. This is a significant benefit to organizations that have taken the leap with digital transformation of their high performance computing needs.

In addition, Artificial Intelligence (AI) plays a significant and transformative role in the development of a modern fighter aircraft. From initial design and simulation to manufacturing, operational capabilities, mission planning, pilot training, and maintenance activities, AI integration results in greater efficiency, precision, and adaptability, ultimately leading to more advanced and capable fighter aircraft.

Here’s an overview of the key stages typically that the aircraft manufacturers must maneuver through, with example simulation software , and AI benefits integrated into the various stages of the development and operational life cycle. Included are some references about how Rescale supports similar workloads in the aerospace industry.

Design and Development

Aerodynamic and Fluid Dynamics Simulation

Engineers use Computer-Aided Design (CAD) software to create 3D models of the aircraft. These models include detailed representations of the airframe, the engine, and other key components required as per the specifications. Initial aerodynamic properties are assessed using Computational Fluid Dynamics (CFD) simulations to optimize the shape for performance and efficiency. CFD simulations are further refined to understand the flow of air over the aircraft in various flight conditions. In addition, Finite Element Analysis (FEA) simulations are used to simulate the structural integrity and stress responses under different loads and conditions. These simulations can be very compute and time intensive and need specialist HPC infrastructure to obtain results in reasonable project times.

To optimize the aerodynamic and structural designs further, AI is used by processing vast amounts of data from simulations to find the most efficient and effective designs. AI helps in generative design, creating multiple design iterations based on specified constraints and performance goals. It also aids in discovering and optimizing new materials with enhanced properties for lightweight and durable airframes. By analyzing material properties and performance data, AI can predict the best composites or alloys for specific parts. Such AI processing workloads, also requires specialist HPC infrastructure which in many cases is based on project needs and needs to scale dynamically.

Example simulation software: ANSYS Fluent, Siemens Simcenter STAR-CCM+, Autodesk CFD, ANSYS Mechanical, MSC Nastran, Dassault Systèmes Abaqus. As an example of similar workloads, see how Exosonic taps into high performance tools that swiftly simulate aerodynamics and analyze airflows, optimizing airplane designs for various flight phases. Gone are the days of costly wind tunnels and lengthy experiments.

Simulation and Testing – Flight Dynamics and Control

Simulation tools are used to integrate and test various subsystems, including avionics, flight controls, propulsion, and weapon systems. Virtual prototypes allow engineers to ensure all systems work together without the  physical prototypes. High-fidelity flight simulators model the aircraft’s performance and handling characteristics. Pilots can “fly” the virtual aircraft to provide feedback on its behavior. Simulations include various scenarios such as takeoff, landing, combat maneuvers, and emergency situations. 

Then, there are environmental conditions like extreme temperatures, humidity, and high-altitude operations that are tested. Cockpit design and ergonomics are optimized using human-in-the-loop simulations, ensuring the layout is intuitive and accessible for the pilots. Usually, a digital twin of the aircraft is created, which is a virtual replica that mirrors the physical prototype, allowing real-time monitoring and analysis during physical tests. Real aircraft components are integrated into the simulation environment to test their performance and interaction with virtual models, making the whole aircraft simulation generate more realistic results. 

Furthermore, AI enhances these simulations by improving the fidelity and efficiency of flight and systems simulations. AI can model complex scenarios and environmental conditions more accurately, providing better data for decision-making. AI-driven predictive analytics help anticipate and mitigate potential design flaws or failures before physical prototypes are built. Automated and autonomous testing processes, powered by AI, significantly speed up validation and verification stages. AI systems can also run extensive test scenarios, analyze the results, and adjust parameters in real-time to optimize performance. That’s quite a lot of simulation work, Phew!!

Example simulation software: MathWorks MATLAB/Simulink, Presagis STAGESee how streamlined access to NASA’s CFD software is empowering aerospace engineers to innovate, maximize efficiency and scalability to drive aerospace projects from concept to completion: Accelerate Aerospace Design Innovation with NASA’s CFD Simulation Applications

Manufacturing

Manufacturing and Assembly

There is a wide variety of simulation software that helps design and optimize manufacturing processes, including assembly lines and quality control procedures. Virtual reality (VR) and augmented reality (AR) are employed to train assembly workers and optimize workflows. Here, AI enhances manufacturing processes through predictive maintenance, quality control, and optimization of production lines. 

AI systems can predict equipment failures and schedule maintenance to avoid downtime. This can also be critical to saving the lives of the pilots. AI-driven robots and automation systems increase precision and efficiency in assembling aircraft components, ensuring higher quality and consistency. AI optimizes supply chain management by predicting demand, managing inventory, and identifying efficient logistics solutions, ensuring parts are available when needed, reducing delays and costs. As you can see, lots of automation goes on in the manufacturing phase which also uses a variety of HPC and AI infrastructure.

Example simulation software: Dassault Systèmes DELMIA, Siemens Tecnomatix, Autodesk Fusion 360

Explore how AI/ML for R&D Can drastically accelerate discoveries like the supercritical airfoil design  [Approx. 8 minutes reading time]: How Artificial Intelligence and Machine Learning Can Accelerate Decades of Aerospace Engineering to Just a Few Hours 

Operational Capabilities – System Integration and Avionics

When looking at the operation capabilities of aircraft, comprehensive mission simulations are conducted to evaluate the aircraft’s performance in realistic combat scenarios, including multi-aircraft operations. These simulations assess not only the aircraft’s capabilities but also tactics, strategies, and pilot training effectiveness. The role of AI here is even more interesting. AI enhances avionics systems by providing real-time data analysis and decision support to pilots. AI can manage and optimize flight paths, fuel consumption, and other critical parameters. AI-based flight control systems improve aircraft stability and handling, especially in challenging conditions. AI is crucial for developing autonomous and unmanned combat aerial vehicles (UCAVs), enabling them to perform complex missions with minimal human intervention. AI supports manned-unmanned teaming, where AI-controlled drones assist manned fighter aircraft, providing additional capabilities and situational awareness. That’s a lot of critical decision factors that are being supported by the employment of AI to assist the pilots.

Example simulation software: Ansys SCADE, Siemens Teamcenter, IBM Engineering Systems Design Rhapsody and similar suites.

Mission Planning and Operational Simulation

Now comes the exciting part, an actual mission practice!

Data from actual flight tests and operational use are fed back into the simulation models to improve accuracy and inform future upgrades. Ongoing simulations support the development of software updates, system enhancements, and new capabilities. AI is heavily employed as it processes and analyzes vast amounts of data from sensors, radar, and other sources in real-time, providing actionable insights to pilots and ground control. AI systems can predict and identify potential threats, optimize mission routes, and suggest tactical maneuvers based on real-time data. Additionally, AI enhances electronic warfare capabilities by quickly adapting to enemy signals and deploying countermeasures. AI-driven defense systems automate threat detection and response, increasing the aircraft’s survivability. These simulations are what provides pilots with real world practice and these simulations are often projected on hollywood screens. (Top Gun fans, anyone?)

Example simulation software: Lockheed Martin Prepar3D, Boeing JMPS (Joint Mission Planning System) and Simlat are some popular suites

Take a look at how engineers are enabled to develop a product in a short timeline leveraging cloud infrastructure and AI methods, then send those details to a physical manufacturing machine in space to produce that product for mission success: From Concept to Cosmos: Rescale’s Role in Advancing Space Technology 

Pilot Training and Simulation

There is a significant use of software and simulation tools used for pilot training, in addition to mission rehearsal.  AI powers advanced flight simulators that provide realistic training environments, adapting to the pilot’s skill level and offering personalized training scenarios. AI-based virtual instructors assess pilot performance and provide real-time feedback, enhancing training effectiveness. AI allows for detailed mission rehearsal simulations, where pilots can practice complex missions in a virtual environment before actual deployment. AI can simulate various enemy tactics and scenarios, preparing pilots for diverse situations.

Example simulation software: Lockheed Martin’s Prepar3D, Quantum3D

Maintenance and Support

Still with me? We are on the final approach, let’s land this blog right! 

Maintenance and Support activities are crucial for the lifecycle of fighter aircrafts,  ensuring their defensive or offensive capabilities remain effective. AI’s role in this phase is predicting when maintenance is needed, based on data from aircraft sensors and historical maintenance records. This reduces downtime and maintenance costs while ensuring aircraft readiness. AI-driven diagnostic tools can quickly identify and troubleshoot issues, streamlining the maintenance process. Regular maintenance, update and support often requires access to specialized HPC software that is a specific generation with its underlying OS/Software components to revisit designs that may need to be supported. Platforms that provide quick and efficient access to a wide range of software tools and versions at the point of a click, can be particularly beneficial in these scenarios, streamlining the maintenance process. 

Example simulation software: MathWorks MATLAB, IBM Watson

Explore the Rescale digital transformation guide for Aerospace industry: Aerospace Industry – Best Practices Guide to Rescale 

Summary

The fighter aircraft lifecycle journey is as complex and security driven as it gets. Leveraging high-performance computing (HPC) and AI to enhance every stage, from design and development to mission planning and maintenance, is a comprehensive approach ensuring the creation of advanced, efficient, and capable fighter aircraft. Platforms like Rescale demonstrate significant value in the aerospace industry. 

With its roots in the aerospace industry, Rescale has become a world leader in “HPC in the Cloud” solutions for aerospace, defense, and emerging technology industries. Rescale provides computational power directly to engineers and scientists tasked with designing these flying engineering marvels, by providing a comprehensive variety of 1200+ HPC and AI Simulation software for the various stages in the aircraft development lifecycle. In addition, Rescale ensures that high security compute needs are met by providing certified ITAR Data Center environments for such HPC and AI workloads via it’s diverse Cloud Computing Infrastructure | Rescale which can be tailored to required regional and compliance regulations.

With  an impressive track record; 9 of the 10 Top Global Aerospace Companies use Rescale, as well as, 8 of the 20 Top “New Space Companies” exploring new aerospace frontiers utilize Rescale platform. 

Next Time, we shall focus on topics such as engine designs in aerospace, which we didn’t get to cover in this blog.