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This paper presents a novel convex optimization-based method for finding the globally optimal solutions of a class of mixed-integer non-convex optimal control problems. We consider problems with non-convex constraints that restrict the…

Optimization and Control · Mathematics 2019-11-21 Danylo Malyuta , Behcet Acikmese

There has been an increasing interest in developing efficient immersed boundary method (IBM) based on Cartesian grids, recently in the context of high-order methods. IBM based on volume penalization is a robust and easy to implement method…

Numerical Analysis · Mathematics 2021-07-22 Jiaqing Kou , Esteban Ferrer

We consider the inverse problem of reconstructing the boundary curve of a cavity embedded in a bounded domain. The problem is formulated in two dimensions for the wave equation. We combine the Laguerre transform with the integral equation…

Numerical Analysis · Mathematics 2025-03-25 Roman Chapko , Leonidas Mindrinos

The computational cost of the boundary-condition-enforced immersed boundary method (IBM) increases in the order of $\mathcal{O}(N^2)$ as the number of Lagrangian points, $N$, increases. This is due to the time-consuming calculation of the…

Fluid Dynamics · Physics 2024-03-25 Manabu Saito , Ryoichi Kurose

A numerical study of an optimal control formulation for a shape optimization problem governed by an elliptic variational inequality is performed. The shape optimization problem is reformulated as a boundary control problem in a fixed…

Optimization and Control · Mathematics 2018-01-22 Raino A. E. Mäkinen

In the context of optimal control, we consider the inverse problem of Lagrangian identification given system dynamics and optimal trajectories. Many of its theoretical and practical aspects are still open. Potential applications are very…

Optimization and Control · Mathematics 2014-03-21 Edouard Pauwels , Didier Henrion , Jean-Bernard Bernard Lasserre

A new approach to the solution of boundary value problems within the so-called fictitious domain methods philosophy is proposed which avoids well known shortcomings of other fictitious domain methods, including the need to generate…

Numerical Analysis · Mathematics 2019-01-17 Daniel Agress , Patrick Guidotti

This paper examines a Markovian model for the optimal irreversible investment problem of a firm aiming at minimizing total expected costs of production. We model market uncertainty and the cost of investment per unit of production capacity…

Probability · Mathematics 2017-01-10 Tiziano De Angelis , Salvatore Federico , Giorgio Ferrari

We propose an immersed boundary scheme for the numerical resolution of the Complete Electrode Model in Electrical Impedance Tomography, that we use as a main ingredient in the resolution of inverse problems in medical imaging. Such method…

Numerical Analysis · Mathematics 2023-05-24 Jérémi Dardé , Niami Nasr , Lisl Weynans

In the present study, a discrete forcing Immersed Boundary Method (IBM) is proposed for the numerical simulation of high-speed flow problems including heat exchange. The flow field is governed by the compressible Navier-Stokes equations,…

Fluid Dynamics · Physics 2023-01-24 Hamza Riahi , Eric Goncalves , Marcello Meldi

The immersed boundary (IB) method has been used as a means to simulate fluid-membrane interactions in a wide variety of biological and engineering applications. Although the numerical convergence of the method has been empirically verified,…

Numerical Analysis · Mathematics 2025-10-09 Alexandre X. Milewski , Charles S. Peskin

Inverse problems arise in a number of domains such as medical imaging, remote sensing, and many more, relying on the use of advanced signal and image processing approaches -- such as sparsity-driven techniques -- to determine their…

Machine Learning · Computer Science 2019-02-01 Jaweria Amjad , Zhaoyan Lyu , Miguel R. D. Rodrigues

The immersed boundary (IB) method is a general mathematical framework for studying problems involving fluid-structure interactions in which an elastic structure is immersed in a viscous incompressible fluid. In the IB formulation, the fluid…

Numerical Analysis · Mathematics 2020-10-01 Yuanxun Bao , Alexander D. Kaiser , Jason Kaye , Charles S. Peskin

Existing approaches to diffusion-based inverse problem solvers frame the signal recovery task as a probabilistic sampling episode, where the solution is drawn from the desired posterior distribution. This framework suffers from several…

Machine Learning · Computer Science 2024-12-24 Henry Li , Marcus Pereira

We develop a new optimisation technique that combines multiresolution subdivision surfaces for boundary description with immersed finite elements for the discretisation of the primal and adjoint problems of optimisation. Similar to wavelets…

Numerical Analysis · Mathematics 2016-01-20 Kosala Bandara , Thomas Rüberg , Fehmi Cirak

Optimal design of experiments for Bayesian inverse problems has recently gained wide popularity and attracted much attention, especially in the computational science and Bayesian inversion communities. An optimal design maximizes a…

Optimization and Control · Mathematics 2023-05-09 Ahmed Attia , Sven Leyffer , Todd Munson

A numerical tool relying on sharp Immersed Boundary Method (IBM) is developed for the analysis of aerospace applications. The method, which is conceived for application using segregated solvers relying on implicit time discretization, uses…

Computational Engineering, Finance, and Science · Computer Science 2025-02-25 M. A. Chemak , E. Constant , M. Meldi

The Immersed Boundary (IB) method of Peskin (J. Comput. Phys., 1977) is useful for problems involving fluid-structure interactions or complex geometries. By making use of a regular Cartesian grid that is independent of the geometry, the IB…

Numerical Analysis · Mathematics 2024-02-06 Brittany J. Leathers , Robert D. Guy

Fluid-structure interactions are central to many bio-molecular processes, and they impose a great challenge for computational and modeling methods. In this paper, we consider the immersed boundary method (IBM) for biofluid systems, and to…

Numerical Analysis · Mathematics 2021-10-13 Yushuang Luo , Xiantao Li , Wenrui Hao

Regularization-based approaches for injecting constraints in Machine Learning (ML) were introduced to improve a predictive model via expert knowledge. We tackle the issue of finding the right balance between the loss (the accuracy of the…

Machine Learning · Computer Science 2020-05-22 Michele Lombardi , Federico Baldo , Andrea Borghesi , Michela Milano