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Recent developments have created differentiable physics simulators designed for machine learning pipelines that can be accelerated on a GPU. While these can simulate biomechanical models, these opportunities have not been exploited for…
To mimic the motion of biological swimmers in bodily fluids, a novel experimental system of micellar solubilization driven active droplets in a visco-elastic polymeric solution is presented. The visco-elastic nature of the medium,…
This paper studies the problem of hybrid holographic beamforming for sum-rate maximization in a communication system assisted by a reconfigurable holographic surface. Existing methodologies predominantly rely on gradient-based or…
The behaviour of microscopic swimmers has previously been explored near large scale confining geometries and in the presence of very small-scale surface roughness. Here we consider an intermediate case of how a simple microswimmer, the…
A new approach for the supercavitating hull optimization was proposed, which combines the CFD simulation and analytical methods. The high-speed penetration into water at the velocity 1 km/s was considered with the fixed body mass and…
Objective: Organ deformation models have the potential to improve delivery and reduce toxicity of radiotherapy, but existing data-driven motion models are based on either patient-specific or population data. We propose to combine population…
Viscoelasticity governs the locomotion strategies of deformable microorganisms, rendering it a fundamental mechanical property of microbial motility and an integral component in the design of envisioned microbots. Recent studies have shown…
Bayesian optimization has emerged as a strong candidate tool for global optimization of functions with expensive evaluation costs. However, due to the dynamic nature of research in Bayesian approaches, and the evolution of computing…
Shape optimization based on the shape calculus is numerically mostly performed by means of steepest descent methods. This paper provides a novel framework to analyze shape-Newton optimization methods by exploiting a Riemannian perspective.…
One of the goals of computer-aided surgery is to match intraoperative data to preoperative images of the anatomy and add complementary information that can facilitate the task of surgical navigation. In this context, mechanical palpation…
Optimization problems with more than one objective consist in a very attractive topic for researchers due to its applicability in real-world situations. Over the years, the research effort in the Computational Intelligence field resulted in…
Swimming cells and microorganisms must often move though complex fluids that contain an immersed microstructure such as polymer molecules, or filaments. In many important biological processes, such as mammalian reproduction and bacterial…
The swimming of a spheroid immersed in a viscous fluid and performing surface deformations periodically in time is studied on the basis of Stokes equations of low Reynolds number hydrodynamics. The average over a period of time of the…
Investigating technical skills of swimmers is a challenge for performance improvement, that can be achieved by analyzing multivariate functional data recorded by Inertial Measurement Units (IMU). To investigate technical levels of…
The swimming of a sphere immersed in a viscous incompressible fluid with inertia is studied for surface modulations of small amplitude on the basis of the Navier-Stokes equations. The mean swimming velocity and the mean rate of dissipation…
This work studies a variational formulation and numerical solution of a regularized morphoelasticity problem of shape evolution. The foundation of our analysis is based on the governing equations of linear elasticity, extended to account…
We conduct experiments with flexible swimmers to address the impact of fluid viscoelasticity on their locomotion. The swimmers are composed of a magnetic head actuated in rotation by a frequency-controlled magnetic field and a flexible tail…
This study explores heated wavy wall shape design in channel flow using machine learning, aiming to minimize temperature variation ($\sigma_T$) while limiting pressure loss ($\Delta p$). A cost function $J$ defined as a product of…
An important step in shape optimization with partial differential equation constraints is to adapt the geometry during each optimization iteration. Common strategies are to employ mesh-deformation or re-meshing, where one or the other…
We efficiently treat bilinear forms in the context of global optimization, by applying McCormick convexification and by extending an approach of Saxena, Bonami and Lee for symmetric quadratic forms to bilinear forms. A key application of…