Daniel Tonelli
Papers
1
Total Citations
14
H-Index
1
About
Daniel Tonelli’s research lies at the critical intersection of structural health monitoring (SHM) and decision-making under uncertainty, with a particular focus on bridging the gap between theoretical SHM benefits and real-world owner skepticism. His most-cited work, “Expected Utility Theory For Monitoring-Based Decision Support System” (2017, 14 citations), directly addresses this challenge by proposing a rigorous, utility-theoretic framework to quantify the value of monitoring data for infrastructure management decisions. Rather than treating SHM as a purely technical exercise, Tonelli reframes it as a decision-support tool, helping owners move beyond intuition and experience to adopt data-driven actions. This contribution is notable for its practical orientation, aiming to increase trust in SHM systems by making their benefits explicit and measurable. While his citation count is still growing, the work’s conceptual novelty—applying expected utility theory to SHM—positions him as a thoughtful voice in the push to make monitoring systems genuinely useful for asset owners. His research is especially relevant for students and practitioners seeking to understand how to translate sensor data into real, defensible management choices.
Research Focus
Key Achievements
Top Papers
- 1Expected Utility Theory For Monitoring-Based Decision Support System14 citations · 2017