Acoustic levitation enables the contactless manipulation of small particles by usingstanding acoustic waves to create stable trapping regions. This technique is valuablein applications where contamination or physical contact must be avoided, such as inmicrofluidics, materials processing, and biomedical research. A single-axis acousticlevitator consists of a transducer and reflector. The performance of an acousticlevitator strongly depends on the geometry of its components.

In this thesis, we investigate the numerical optimization of a single-axis acousticlevitator, focusing on one of its key components, the shape of the reflector. Theacoustic field is modeled using the Helmholtz equation, which is solved using the finiteelement method (FEM) with absorbing boundary conditions and perfectly matchedlayers (PML) to simulate unbounded domains. The Gor’kov potential, derived fromthe pressure field, is used as the objective function to quantify the effectiveness of theacoustic trap in a predefined region.

The reflector surface is parametrized using a sine basis, and the shape optimization iscarried out through sensitivity analysis based on the adjoint method. This approachprovides the gradient of the Gor’kov potential with respect to shape parameters,allowing for iterative updates of the reflector design to minimize the objective functionin the trapping region.

Numerical simulations show that the optimized reflector geometry significantlyenhances the acoustic trap by creating deeper and more localized Gor’kov potentialwells. This confirms the feasibility of using shape calculus and adjoint-basedoptimization techniques for improving acoustic levitator performance.