Lightweight Design Optimization Using Quantum Annealing

One of todays key industrial and environmental challenges is producing components that are lighter without compromising their strength. This project pioneers a new approach, using quantum computing to optimize lightweight designs. Modern industries such as aviation, automotive, and mechanical engineering constantly seek to make components lighter without compromising strength or performance. Lighter designs reduce material use, save energy, and help protect the environment. Achieving this balance between low weight and high performance is the goal of lightweight design optimization (LDO). However, finding the ideal lightweight design can be an extremely complex task. Even when using computer-based optimization methods, these must evaluate and compare countless possible configurations defined by different shapes or material choices. This requires enormous computing power and often leads to results that are not truly optimal. This means that traditional computers struggle with such tasks because they cannot efficiently explore the vast space of possible designs. To address this issue, our research explores a completely new approach: applying quantum computing, specifically the method known as quantum annealing (QA). Unlike classical computers, quantum systems can leverage the principles of quantum mechanics to explore multiple design options simultaneously and identify the overall best solution within a short period of time. This can enable engineers to develop improved designs more quickly and with less computational effort. To take advantage of QAs potential in the context of LDO, the project investigates how to formulate engineering design problems so that they can be solved efficiently on quantum hardware. This involves expressing the optimization task in a mathematical form suitable for currently available quantum computers. Since QA is still an emerging technology, we also study how to address its current limitations, such as limited robustness or constraints on problem size and complexity. The projects innovation lies in combining the physical principles of structural mechanics with advanced computing architectures, such as QA. By uniting these two aspects in a single formulation, we aim to rapidly identify the best lightweight designs, without relying on traditional, time-consuming simulation-based methods that explore the design space step by step. Ultimately, this research can open a new chapter in computer-aided design: enabling the creation of lighter, stronger, and more sustainable components through the power of quantum technologies.