Joint publication of DLR and the RISK.twin project in CAMES

3 August 2026

We are happy to announce our new publication in the journal of Computer Assisted Methods in Engineering and Science, entitled "Goal-Oriented Optimal Sensor Placement for PDE-Constrained Inverse Problems in Crisis Management" by Marco Mattuschka, Noah an der Lan, Max von Danwitz, Daniel Wolff, and Alexander Popp, which is a joint work of the DLR Institute for the Protection of Terrestrial Infrastructures and the dtec.bw project RISK.twin.

In this paper, we present a novel framework for goal-oriented optimal static sensor placement and dynamic sensor steering in PDE-constrained inverse problems, utilizing a Bayesian approach accelerated by low-rank approximations. The framework is applied to airborne contaminant tracking, extending recent dynamic sensor steering methods to complex geometries to improve computational efficiency. A C-optimal design criterion is employed to strategically place sensors, minimizing uncertainty in predictions. Numerical experiments validate the approach’s effectiveness for source identification and monitoring, highlighting its potential for real-time decision-making in crisis management scenarios.

Mattuschka, M., An der Lan, N., von Danwitz, M., Wolff, D., & Popp, A. (2026). Goal-oriented optimal sensor placement for PDE-constrained inverse problems in crisis management. Computer Assisted Methods in Engineering and Science, 33(2), 147–170. DOI (Open Access)