activity
20242026
collaborators

5 papers

math.OC2026

Data assimilation via model reference adaptation for linear and nonlinear dynamical systems

Benedikt Kaltenbach, Christian Aarset, Tram Thi Ngoc Nguyen

We address data assimilation for linear and nonlinear dynamical systems via the so-called model reference adaptive system. Continuing our theoretical developments, we deliver the f…

math.OC2025

FEM-based A-optimal sensor placement for heat source inversion from final time measurement

Christian Aarset, Tram Thi Ngoc Nguyen

Within the field of optimal experimental design, \emph{sensor placement} refers to the act of finding the optimal locations of data collecting sensors, with the aim to optimise rec…

math.OC2025

Global optimality conditions for sensor placement, with extensions to binary low-rank A-optimal designs

Christian Aarset

The \emph{sensor placement problem} for stochastic linear inverse problems consists of determining the optimal manner in which sensors can be employed to collect data. Specifically…

math.OC2024

A global optimum-informed greedy algorithm for A-optimal experimental design

Christian Aarset

Optimal experimental design (OED) concerns itself with identifying ideal methods of data collection, e.g.~via sensor placement. The \emph{greedy algorithm}, that is, placing one se…

math.NA2024

Bi-level regularization via iterative mesh refinement for aeroacoustics

Christian Aarset, Tram Thi Ngoc Nguyen

In this work, we illustrate the connection between adaptive mesh refinement for finite element discretized PDEs and the recently developed \emph{bi-level regularization algorithm}.…