The Future of Simulation Design and the Real-World Impact of Quantum Computing
In engineering, understanding how different elements of physics interact can make all the difference between a crappy design and superior performance. Whether designing the heating element of a kettle, the jet engine of an airplane or even a turbine for a power station, engineers must first simulate and analyze how their creation will respond to different extremes of temperature, pressure, noise and vibration.
Today, Computational Fluid Dynamics (CFD) is used extensively across industrial applications for simulating the effects of gases and liquids, as well as the flow and exchange of heat, over a design. CFD is critical to how automotive companies design more streamlined vehicles and how aerospace companies perfect the flow of air across a plane wing.
But with quantum computing on the horizon (though still possibly several years away), CFD could change overnight. How will the next evolution of computing power impact CFD, and is the engineering industry ready for this change?
The Next Stage of CFD
CFD involves computationally demanding, complex simulations of physical phenomena that require intricate numerical solutions. Increasing the variables considered can improve the accuracy of the simulation and thus the efficiency of the final design, but it takes classical computers more and more time to process. Even today’s most powerful supercomputers can only simulate these interactions to a certain degree of accuracy.
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Creating more precise, more sophisticated CFD simulations is not only important for improving advanced equipment design, such as by optimizing aerodynamics and thermodynamics, but also to increase their reliability and sustainability. With many companies pursuing net zero carbon emissions, manufacturing more environmentally friendly products in the future—ones that are more efficient, use less fuel, require less material to make and last longer before breaking or needing to be replaced—is critical. Unfortunately, the enhancements to the sophistication of CFD simulations needed to achieve such net-zero goals are already stretching the limits of classical supercomputers.
And because supercomputing resources are limited, companies must often be selective about which designs and applications they analyze with the most sophisticated CFD simulations. Often, only the most critical components of a design are simulated.
But with the advent of quantum computing, this can change. The nature of quantum computing means that solving this type of problem—the processing of large numbers of linear equations—is much less resource-intensive: It can scale more easily as the number of variables increases. In other words, a simulation problem that would challenge a supercomputer to solve could instead be solved much more easily, readily and quickly using a quantum computer.
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Increasing the efficiency of the simulation, and lowering the resource intensiveness of simulations, massively expands the possibilities of what can be simulated and makes larger CFD simulations more approachable. Businesses that need to use CFD simulations can consider analyzing their whole designs, not just the most critical components. They can do it for more applications, be less hesitant about the costs involved and the time required to produce results, and accelerate the development of new products.
Achieving Quantum Advantage
While a quantum computer capable of solving a problem faster than a classical computer—known as quantum advantage—may still be several years away, companies need to be prepared for when this day comes. Quantum algorithms that can perform CFD simulations have already been created.
The most well-known is the HHL algorithm, named after creators Harrow, Hassidim and Lloyd. This fundamental quantum algorithm is designed to solve linear sets of equations and holds the promise of speedier computations than its classical counterparts. The level of accuracy of a circuit running the algorithm is influenced by various factors, including different quantum function implementations, the number of qubits and the circuit’s depth. However, research by NVIDIA simulating the execution time of the algorithm shows that increasing the number of GPUs employed in the quantum simulator with a fixed number of qubits can reduce computation time by an order of magnitude.
Alongside these developments, many companies have taken steps to ensure they have the capabilities to benefit from quantum advantage when it arrives. UK manufacturer Rolls-Royce announced last year that, using NVIDIA’s quantum computing platform, it had designed and simulated the world’s largest quantum computing circuit for CFD—a circuit that measures 10 million layers deep with 39 qubits.
Rolls-Royce intends to use the circuit to model the performance of jet engine designs in simulations that combine classical and quantum computing methods. This will help to reduce the cost and computational challenges of designing jet engines. In the long term, this may enable the company to design more sustainable aviation technology.
A Greener, Safer World
Not only could better simulations help companies design more energy-efficient and sustainable products, but they can also make them safer.
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In today’s world, engineers must build test models of a design to perform safety checks on it before it can go into production. Often, these models will fail because something may have been missed in the calculations. But with better, more accurate simulations, able to process the interactions of more variables simultaneously, many safety checks could be performed computationally, reducing the upfront costs of safety checks as well as saving time. This could give manufacturers more confidence in the safety of their designs and get them into production faster.
Quantum-enhanced physics simulations hold huge potential. Manufacturers need to consider how they will integrate quantum calculations into their design process so they can be ready when the quantum advantage arrives.
